The aim of this study is to develop a corporate financial distress prediction model based on financial ratios for listed companies across various sectors in India using binary logistic regression technique. For this, 51 companies listed on Bombay Stock Exchange (BSE) and/or National Stock Exchange (NSE) has been chosen as a sample study. The selected companies were bifurcated in two groups based on financial ratios. The explanatory variables were divided into four categories such as liquidity, solvency, efficiency and profitability ratios based on standard practices followed by financial analysts to draw reliable insights. The t-test was used to check the statistical significance of each independent variable for two groups that is insolvent and solvent. The results of t-test were found statistically non-significant (p>0.05) at 5% level of significance in case of fixed assets turnover ratio, interest coverage ratio, number of days in working capital ratio, quick ratio and return on net worth ratio where as others independent variables were found statistically significant (p<0.05).The variance inflation factor (VIF) was used for measuring multicollinearity. The independent variables having VIF value less than 5 were used for fitting binary logistic regression model to predict the corporate financial distress. The forecast strength of the logistic regression model was found 96.80% and the goodness of fit of the model was checked by using the Hosmer and Lemeshow test. It is found that the interest coverage ratio, net profit margin and number of days in working capital ratio are significant predictors of corporate insolvency. The findings of the present study can be used to assist in financial decision-making for various stakeholders.