What Is the Altman Z-Score? Formula and Interpretation

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The Altman Z-score is a credit-strength formula that combines five financial ratios into a single number to estimate a company’s likelihood of bankruptcy, typically within about two years. A higher score points to a sounder balance sheet and earnings base. A lower score points to financial distress. NYU Stern professor Edward Altman developed the model in 1967 and published it in 1968. The original version was built for publicly traded manufacturing companies, and later variants extend it to private firms, non-manufacturers and emerging-market issuers.

How the Altman Z-Score Works

Altman used multiple discriminant analysis, a statistical method that finds the weighted combination of variables that best separates two groups. On a sample of 66 manufacturing companies, half bankrupt and half not, the model picked five ratios and coefficients that split the two groups as cleanly as possible.

Despite the name, it is not a statistical z-score, which measures how many standard deviations a value sits from a mean. The Altman Z-score is a weighted sum of ratios.

All five inputs come from a company’s annual financial statements (the 10-K for U.S. public companies), plus its market capitalization.

Altman Z-Score Formula

The original formula is:

Z = 1.2A + 1.4B + 3.3C + 0.6D + 1.0E

• A = working capital / total assets. Measures short-term liquidity relative to the size of the firm. Shrinking working capital often shows up before a failure.
• B = retained earnings / total assets. Captures cumulative profitability and, indirectly, company age, since young firms have had less time to build retained earnings.
• C = EBIT / total assets. Earnings before interest and taxes relative to assets, a measure of how productively the asset base generates operating profit. It carries the largest weight.
• D = market value of equity / total liabilities. Shows how far the company’s market value could fall before liabilities exceed it.
• E = sales / total assets. Asset turnover, a measure of how much revenue the asset base produces.

Some sources show the coefficients as 0.012, 0.014, 0.033, 0.006 and 0.999. That version expects the first four ratios entered as percentages (15 instead of 0.15) and produces the same score.

Interpreting the Altman Z-Score

For the original public manufacturing model, the standard zones are:

These cutoffs are often rounded to 1.8 and 3. The score has no upper limit: a company with a market capitalization many times its total liabilities can post a D ratio high enough to push Z above 10 or even 30, which says more about investor optimism than about operating performance. The score can also be negative when working capital, retained earnings or EBIT turn negative.

In a 2019 retrospective titled “50 Years of the Altman Score,” Altman noted that recent data suggest 0, not 1.8, is the level at which investors should become seriously concerned. Many analysts still use the original zones, so check which convention a screen or report applies.

Altman’s accuracy reviews of distressed companies from 1969 to 1975 (86 firms), 1976 to 1995 (110) and 1996 to 1999 (120) found the model classified bankrupt companies correctly 82% to 94% of the time. He has also mapped Z-score ranges to bond-rating equivalents, so a score can be translated into an implied credit rating.

Example of the Altman Z-Score

Hypothetical company, figures in millions: total assets $1,000; working capital $150; retained earnings $300; EBIT $120; market value of equity $600; total liabilities $600; sales $1,100.

• A = 150 / 1,000 = 0.15 → 1.2 × 0.15 = 0.180
• B = 300 / 1,000 = 0.30 → 1.4 × 0.30 = 0.420
• C = 120 / 1,000 = 0.12 → 3.3 × 0.12 = 0.396
• D = 600 / 600 = 1.00 → 0.6 × 1.00 = 0.600
• E = 1,100 / 1,000 = 1.10 → 1.0 × 1.10 = 1.100

Z = 2.70, in the grey zone.

Now assume the share price halves and nothing else changes. Market value of equity drops to $300, D becomes 0.50, and its weighted contribution falls to 0.30. The score drops to about 2.40 although sales and profits are unchanged. This is why analysts compare the score over several periods rather than relying on one reading.

Variants: Z’ and Z’’

Because the original model was estimated on public manufacturers, Altman re-estimated it for other cases.

Z’ (private firms) replaces market value of equity with book value of equity in the D ratio: Z’ = 0.717A + 0.847B + 3.107C + 0.420D + 0.998E. Distress is below 1.23 and safe is above 2.90.

Z’’ (non-manufacturers and emerging markets) drops the sales/total assets ratio, since asset turnover varies widely by industry, and uses book equity in D: Z’’ = 6.56A + 3.26B + 6.72C + 1.05D. Distress is below 1.10 and safe is above 2.60. For emerging-market corporate bonds, Altman added a constant of 3.25 so that the scores line up with bond-rating equivalents.

In 2012 Altman released Altman Z-score Plus, an updated credit-risk framework for public and private, manufacturing and non-manufacturing, and U.S. and non-U.S. companies.

Mixing these versions is a common error. A Z’’ of 2.0 and an original Z of 2.0 do not mean the same thing, because the coefficients and cutoffs differ.

How the Z-Score Is Used

Credit analysts and lenders use the Z-score as a quick screen of default risk alongside ratings and covenant analysis. Equity investors use it to flag companies whose balance sheets may not support their valuations, and some treat a score drifting toward the distress zone as a reason to sell or short. Managers can use it to see which ratio is dragging the score down, such as thin working capital, heavy leverage or weak returns on assets.

The score drew attention around the 2008 financial crisis. Altman found that the median Z-score of the companies he studied in 2007 was 1.81, equivalent to a B credit rating, implying that half of those firms were highly distressed. He expected a credit market meltdown driven by corporate defaults. The crisis began in mortgage-backed securities instead, but corporate defaults followed in 2009 at the second-highest rate on record.

Limitations of the Altman Z-Score

• Financial companies: banks, insurers and other financial firms have balance sheets that the ratios do not read correctly, and the model was not built for them.
• Accounting quality: the inputs are reported figures. Aggressive revenue recognition, off-balance-sheet obligations or one-off gains can inflate the score.
• Market noise: in the original formula, share price swings move the D ratio without any change in fundamentals.
• Industry and era: coefficients estimated on 1960s U.S. manufacturers may not fit asset-light, high-growth or loss-making companies, which is part of why Altman moved the distress line toward 0.
• Cash flow: the score uses no cash flow measure, so a firm with adequate ratios but a looming debt maturity it cannot refinance may still screen as acceptable.

Altman Z-Score vs. Other Distress Models

The Z-score is one of several accounting-based bankruptcy predictors. The Zmijewski X-score uses probit regression on three ratios (return on assets, debt to assets and the current ratio) and outputs a probability rather than zones. The Ohlson O-score uses logistic regression on nine factors, including company size. The Piotroski F-score answers a different question: it is a 0 to 9 checklist of improving fundamentals used to select value stocks, not a bankruptcy model. None of these maps directly onto another, so a stock can look acceptable on one and weak on another.

The Bottom Line

Lenders, credit analysts, equity investors and managers can use the Z-score as a quick screen of default risk, provided they match the right version to the company. It does not fit banks or insurers, ignores cash flow and swings with share prices in the original formula. Tracking the score over several periods and pairing it with ratings, covenant analysis and accounting checks gives a more reliable read than any single result.