This study investigates the applicability of logistic regression in predicting financial distress among 150 nonfinancial companies listed on the Amman Stock Exchange (ASE) over the period 2021–2023. The analysis begins with 13 financial ratios traditionally associated with financial health and corporate failure. Companies were labeled as distressed or non-distressed, according to Altman’s [J Financ 23(4):589–609, 1968] Z-score model. The initial logistic regression model revealed that only four financial ratios—return on capital, return on equity, total debt to capital, and total liabilities to assets—made statistically significant contributions to predicting financial distress. A refined model using only these variables demonstrated strong explanatory power, with a Nagelkerke R-squared (R2) of 55% and an overall classification accuracy of 84.3%. Multicollinearity diagnostics confirmed that the model was statistically sound. The results underscore the predictive value of profitability and leverage ratios and provide a practical tool for early warning systems in emerging markets. The results carry significant implications for investors, regulators, and organizational stakeholders concerned with financial risk assessment and firm stability, especially in an emerging market like Jordan.