Altman Z-Score: What Bankruptcy Risk Models Can and Cannot Tell You
An Altman Z-Score of 1.51 is not a 1.51% probability of bankruptcy.
It is not a countdown, a credit rating, or proof that a company will fail. It is the output of a statistical classification formula that combines five ratios into a financial-distress profile.
That distinction is easy to lose. A stock platform displays one number, places it in a colored zone, and makes the result look self-explanatory. But the interpretation depends on which Altman formula was used, whether the company fits that formula, how each input was defined, when the market price was measured, and what unusual events affected the annual accounts.
The useful question is not simply, “Is the Z-Score high or low?”
It is: “What evidence pushed the company into this zone, and what important questions remain unanswered?”
The model classifies a financial profile; it does not observe the future
Edward Altman introduced the original Z-Score in his 1968 Journal of Finance paper, Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy.
The research combined financial ratios with multiple discriminant analysis. Altman’s initial sample contained 66 manufacturing companies divided between bankrupt and non-bankrupt groups. The formula was designed to find a weighted combination of ratios that separated those historical profiles.
That origin explains both the model’s usefulness and its limits.
The score can identify whether a company’s current inputs resemble a profile associated with stronger or weaker financial condition under the model. It cannot directly observe future refinancing decisions, government support, asset sales, capital raises, operational recoveries, litigation outcomes, or shocks that have not yet entered the data.
Altman himself later described the original model as mainly relevant to manufacturing companies in a CFA Institute interview. He also explained that later versions were developed for different populations.
Inside the broader stock analysis models comparison, Altman therefore belongs in the Financial Health & Risk family. It asks a narrower question than valuation, growth, momentum, or business-quality models:
Does this company’s financial structure resemble a lower- or higher-distress profile under the selected Altman formula?
The wording matters. “Higher distress profile” is supportable. “This company will go bankrupt” is not.
Choose the Altman variant before calculating anything
“Altman Z-Score” can refer to more than one model.
| Variant | Intended setting | Important distinction |
|---|---|---|
Original Z | Publicly traded manufacturing companies | Uses market value of equity and includes sales divided by total assets |
Z' | Private manufacturing companies | Replaces market equity with book equity and uses recalibrated coefficients and thresholds |
Z'' | Non-manufacturing and broader industrial settings | Removes the sales-to-assets factor and recalibrates the remaining model |
These variants are not interchangeable. Changing the formula changes the meaning of the resulting number and the thresholds used to interpret it.
StockGeniuses uses the original five-factor public-company form. That choice is appropriate for a worked Boeing example because Boeing is a listed manufacturer. It would be much harder to defend for a bank, and it would require stronger model-fit caution for an asset-light software company.
This formula-selection step reflects a broader rule for reading any stock analysis model: establish the model’s purpose, eligible population, inputs, and failure behavior before treating its output as evidence.
Five ratios build the StockGeniuses Z-Score
The locked StockGeniuses formula is:
Z = 1.2X1 + 1.4X2 + 3.3X3 + 0.6X4 + 1.0X5
Altman’s original expression uses an X5 coefficient of 0.999. StockGeniuses uses the locked rounded coefficient of 1.0. That small implementation detail should be disclosed rather than hidden, even though it rarely changes a practical zone classification by itself.
X1: Working capital divided by total assets
X1 = (Current Assets - Current Liabilities) / Total Assets
X1 measures short-term liquidity relative to the company’s asset base. Positive working capital increases the score; negative working capital reduces it.
The ratio is not a universal verdict on liquidity quality. Some business models can operate with structurally low or negative working capital because customers pay before suppliers must be paid. Others face genuine near-term pressure. The formula records the condition but does not explain the operating reason.
X2: Retained earnings divided by total assets
X2 = Retained Earnings / Total Assets
X2 compares accumulated retained profits with the asset base. A mature company that has funded more of its development through retained earnings will usually score differently from a younger or repeatedly loss-making company that has relied more heavily on external capital.
Retained earnings can also be affected by dividends, losses, accounting adjustments, and corporate history. It is not the same as cash available today.
X3: EBIT divided by total assets
X3 = EBIT / Total Assets
X3 measures operating earnings relative to the assets employed. It receives the largest coefficient in the original formula.
Input mapping matters here. Providers do not always use the word EBIT consistently. The Boeing calculation below maps GAAP earnings from operations to the fiscal-year EBIT input, consistent with the operating-income convention in the StockGeniuses data contract. A calculation built from pretax income plus gross interest expense could produce a different number.
X4: Market value of equity divided by total liabilities
X4 = (Shares Outstanding * T-1 Adjusted Close) / Total Liabilities
X4 compares the market value of common equity with total liabilities. It is not book equity divided by debt.
This makes the original Z-Score a hybrid model. Four inputs are anchored in the latest annual statements, while one important component changes with the share price. Market confidence is therefore part of the calculation.
X5: Revenue divided by total assets
X5 = Revenue / Total Assets
X5 measures asset turnover: how much annual revenue the company generates for each dollar of assets.
Asset turnover varies substantially by industry. A retailer, software company, utility, and aircraft manufacturer can have very different normal asset structures. That industry sensitivity was one reason Altman’s later Z” model removed the sales-to-assets variable.
These five ratios are compressed inputs. The Core Metrics layer still matters because a model cannot preserve every detail contained in liquidity, profitability, leverage, and operating-efficiency evidence.
The three zones are ordinal risk classifications
StockGeniuses applies these locked boundaries:
| Z-Score | StockGeniuses classification |
|---|---|
Z > 2.99 | Low Distress Risk |
1.81 <= Z <= 2.99 | Grey Zone |
Z < 1.81 | High Distress Risk |
The endpoint treatment is explicit: exactly 1.81 and exactly 2.99 remain in the Grey Zone.
The zones are ordinal, not linear. A score of 3.0 is not twice as financially healthy as 1.5. A change from 1.79 to 1.82 crosses a displayed boundary but represents only a small movement in the underlying index.
Distance from the threshold still matters. So does the component responsible for the movement.
Calling the upper range “Low Distress Risk” is also more disciplined than calling it “safe.” A company can sit above 2.99 and still face fraud, litigation, technological disruption, customer concentration, regulatory action, or a sudden liquidity event that the formula does not contain.
Eligibility and data quality come before the zone
StockGeniuses requires:
- current assets;
- current liabilities;
- total assets above zero;
- retained earnings;
- fiscal-year EBIT;
- total liabilities above zero;
- fiscal-year revenue;
- shares outstanding above zero;
- a positive T-1 adjusted close;
- a non-financial industry classification.
Every required input must be present and valid. The system does not calculate a partial Z-Score when one factor is missing. It returns Not Meaningful.
Financial institutions are also a hard exclusion. Banks and similar firms use leverage, liquidity, deposits, and regulatory capital differently from industrial companies. Forcing the original formula onto them can produce a number without producing a valid comparison.
Non-financial does not automatically mean ideal. Asset-light companies, businesses undergoing major transformations, and companies with unusual balance-sheet structures still require model-fit caution.
Boeing example: a dated distress-risk snapshot
The worked example uses Boeing’s fiscal 2025 Form 10-K, filed January 30, 2026.
Analysis snapshot: July 23, 2026
Financial period: Fiscal year ended December 31, 2025
Price input: July 22, 2026 adjusted close
Method: Locked StockGeniuses original public-company Z-Score
Boeing is suitable for this demonstration because it is a publicly traded manufacturer and its filing contains every required financial input. The example does not claim that Boeing will enter bankruptcy, that its shares are cheap or expensive, or that the score captures developments after the fiscal year-end.
Dollar amounts below are in millions except the per-share price.
| Input | Boeing value | Source treatment |
|---|---|---|
| Current assets | $128,459 | FY2025 balance sheet |
| Current liabilities | $108,115 | FY2025 balance sheet |
| Total assets | $168,235 | FY2025 balance sheet |
| Retained earnings | $17,252 | FY2025 balance sheet |
| EBIT | $4,281 | FY2025 GAAP earnings from operations |
| Total liabilities | $162,778 | FY2025 balance sheet |
| Revenue | $89,463 | FY2025 statement of operations |
| Shares outstanding | 784.70 | FY2025 common shares, millions |
| Adjusted close | $208.65 | July 22, 2026 |
The fiscal-year shares and price were cross-checked through AlphaQuery’s Boeing financial data, which reported 784.70 million FY2025 common shares and a July 22 adjusted close of $208.65.
Annual financials and current price do not share the same date. That is intentional under the model contract: latest completed fiscal-year statements are combined with the T-1 market price. The snapshot date must remain visible so readers do not mistake the output for a timeless company fact.
Rebuilding Boeing’s score from five contributions
First calculate working capital and market value of equity:
Working Capital = 128,459 - 108,115 = 20,344
Market Value of Equity = 784.70 * 208.65 = 163,727.655
Then calculate each ratio and weighted contribution. Displayed values are rounded, but the final result uses unrounded arithmetic.
| Component | Calculation | Ratio | Weighted contribution |
|---|---|---|---|
| X1 | 20,344 / 168,235 | 0.1209 | 1.2 * X1 = 0.1451 |
| X2 | 17,252 / 168,235 | 0.1025 | 1.4 * X2 = 0.1436 |
| X3 | 4,281 / 168,235 | 0.0254 | 3.3 * X3 = 0.0840 |
| X4 | 163,727.655 / 162,778 | 1.0058 | 0.6 * X4 = 0.6035 |
| X5 | 89,463 / 168,235 | 0.5318 | 1.0 * X5 = 0.5318 |
The result is:
Z = 0.1451 + 0.1436 + 0.0840 + 0.6035 + 0.5318
Z = 1.5079
Rounded for display, Boeing’s snapshot Z-Score is 1.51, which falls below the locked 1.81 threshold and enters the High Distress Risk zone.
That is the mechanical result. Interpretation begins after the calculation, not before it.
Boeing’s 1.51 contains five different stories
The headline score does not show which factors carried the result.
Boeing had positive working capital, so X1 added approximately 0.145. Retained earnings were positive relative to total assets, adding another 0.144. Reported operating earnings were positive but small relative to the asset base, contributing only about 0.084 after weighting.
The two largest contributions came from market equity relative to liabilities and revenue relative to assets:
- X4 contributed approximately
0.604; - X5 contributed approximately
0.532.
Together, those two components supplied roughly three-quarters of the final score. More precisely, their unrounded contributions account for approximately 75.3% of the total. A reader who sees only 1.51 cannot see that concentration.
The pattern also differs from a Piotroski result. The Piotroski F-Score asks whether annual accounting conditions improved or deteriorated. Altman combines levels from one fiscal-year profile with a current market input. One is primarily a trajectory diagnostic; the other is a structural distress classification.
Neither replaces the other.
One component can change before the annual statements do
Boeing’s X4 uses the July 22 share price. Hold shares and total liabilities constant and a 10% price move changes X4 by 10%.
At this snapshot, X4 contributes approximately 0.6035 to the total. A 10% share-price move would therefore change the Z-Score by about:
0.6035 * 10% = 0.0604
The latest annual working capital, retained earnings, EBIT, liabilities, revenue, and assets have not changed. The displayed Z-Score has.
This does not make X4 a defective input. Market equity can contain timely information about investors’ willingness to capitalize the company relative to its obligations. But it means the score should always be dated, and movement should be traced to its source.
A company near 1.81 or 2.99 could cross a zone boundary because of price alone. The zone would change before a new annual report supplied any fresh accounting evidence.
Reported EBIT can be mechanically valid and economically unusual
Boeing’s 2025 statement reports $4.281 billion of earnings from operations. The same filing reports $9.672 billion of net gains on dispositions, including a $9.566 billion gain from the Digital Aviation Solutions divestiture.
That gain is inside reported operating earnings.
The locked Z-Score uses the reported fiscal-year EBIT input. It does not normalize one-time items, and this article does not substitute an adjusted number after seeing the result. Doing so would create a different, undocumented model.
Yet a serious interpretation cannot stop at formula compliance. The positive X3 contribution does not mean recurring aircraft operations generated the entire reported EBIT figure. The filing requires a separate earnings-quality review.
This is an important distinction between calculation validity and evidence quality:
- the input can satisfy the mechanical contract;
- the economic story behind the input can still require investigation.
An analyst may calculate a separately labeled sensitivity with an adjusted operating figure, but it should never be presented as the locked model result. The model is a screen. It is not accounting due diligence.
Evidence the Z-Score brings forward
Used carefully, the score can do several useful jobs.
It combines several forms of financial pressure
Liquidity, accumulated profitability, operating productivity, liability coverage by market equity, and asset turnover do not describe identical risks. Combining them can reveal a weak overall profile that no single ratio captures alone.
It creates a consistent first-pass screen
The formula can help investors prioritize which companies deserve deeper distress analysis, provided the same variant and input definitions are used consistently.
It exposes the components that deserve follow-up
A low total caused by negative working capital presents a different research problem from one caused by accumulated losses or weak operating earnings. Reopening the total guides the next question.
It can support historical monitoring
Calculating the same version over comparable annual periods can show whether the company’s profile moved toward or away from a boundary. The broader historical performance review is still needed to determine whether that movement reflects a durable trend, one unusual year, or a changed business structure.
Questions the Z-Score leaves unresolved
The output does not complete the investment case.
| The score can surface | The score cannot establish |
|---|---|
| Short-term working-capital position relative to assets | Exact liquidity available on a future date |
| Accumulated retained earnings relative to assets | Current cash generation or earnings durability |
| Reported EBIT relative to assets | Recurring operating quality after unusual items |
| Market equity relative to total liabilities | Ability to refinance every obligation |
| Revenue relative to assets | Competitive advantage or attractive reinvestment |
| Position within a model zone | A literal bankruptcy probability or date |
| A distress-screening priority | Whether the stock is undervalued or likely to outperform |
The model also does not capture every source of support or fragility. Debt maturities, covenant terms, access to capital markets, undrawn credit, customer advances, government relationships, pension obligations, legal exposure, asset salability, and management responses may all matter.
That is why the underlying financial strength and risk signals remain necessary. A composite score should direct attention toward the balance sheet and cash-flow structure, not replace them.
Nor does survival capacity prove durable business quality. Competitive position, pricing power, customer dependence, execution, and reinvestment economics belong in a separate business-quality evaluation.
Model fit can fail even when the arithmetic works
Several situations require particular caution:
- Financial institutions: StockGeniuses treats the original model as Not Meaningful because regulated capital, deposits, and financial leverage do not map cleanly to industrial-company ratios.
- Asset-light companies: A small asset denominator can create ratios that do not compare sensibly with manufacturers.
- Industry comparisons: X5 is highly sensitive to normal industry asset turnover.
- Major transformations: Acquisitions, disposals, restructurings, and accounting changes can make one annual snapshot unlike the prior company.
- Unusual operating items: Reported EBIT can contain gains or charges that are mechanically valid but not representative.
- Stale statements: Annual accounts can lag major developments while X4 continues moving with price.
- Threshold proximity: A tiny input change can move a company from one labeled zone to another without a large economic change.
The response to these limits is not to discard every distress model. It is to state when the model is appropriate, preserve its source dates, and refuse to force certainty from the result.
A disciplined way to use the Altman Z-Score
Use the following sequence:
- Identify the formula. Confirm whether the result is original
Z, private-companyZ', or non-manufacturerZ''. - Check eligibility. Do not apply the original public-manufacturer model to a financial institution.
- Confirm the dates. Separate the fiscal-year statement date from the T-1 market-price date.
- Audit the input definitions. Verify EBIT, total liabilities, shares, and market value of equity in particular.
- Recalculate without intermediate rounding. A displayed total should be reproducible.
- Locate the zone and distance from its boundary. Do not treat adjacent values as radically different companies.
- Reopen the weighted contributions. Determine which components drove the total.
- Investigate unusual accounting. Look for divestitures, impairments, restructuring, acquisitions, and other events.
- Compare with other risk evidence. Review cash flows, debt maturities, coverage, liquidity, and financial trajectory.
- State the non-conclusion. The score does not determine value, future return, or an investment action.
For Boeing, this process produces a careful conclusion: the FY2025 and July 22 market inputs generate an original-form Z-Score of approximately 1.51, placing the snapshot in StockGeniuses’ High Distress Risk zone. Market equity and asset turnover provide most of the positive contribution, reported EBIT is affected by a large divestiture gain, and the result does not state that bankruptcy will occur.
The output is a reason to investigate the financial structure more closely. It is not permission to stop thinking.
Let the zone open the next question
The Altman Z-Score remains useful because it compresses five distinct signals into a consistent distress screen. Its age and simplicity do not make it worthless. They make its scope and assumptions especially important.
The mistake is asking the number to do work it was never designed to do.
A low Z-Score can identify a financial profile that deserves scrutiny. A high Z-Score can reduce one form of concern. Neither result values the company, predicts the stock, proves business quality, or removes uncertainty.
Keep the formula visible. Keep the dates attached. Reopen the components. Then place the result inside a systematic stock analysis process that can examine what the model necessarily leaves out.
This article is educational and does not provide investment advice or a recommendation regarding The Boeing Company or any other security.