: This paper develops a logistic regression model to predict bank bankruptcy in Ukraine during wartime, a period of heightened economic instability. Utilizing 22 financial indicators from the National Bank of Ukraine, the analysis identifies administrative expenses relative to assets and interest income relative to assets as significant predictors of bank failure. After applying correlation analysis and stepwise elimination, a logistic regression model was constructed, demonstrating a high degree of statistical significance (p < 0.001) and an overall classification accuracy of 88.9%. The model, represented by a logistic equation, allows for the calculation of bankruptcy probability, providing a valuable tool for early risk assessment and regulatory intervention in the Ukrainian banking sector amidst ongoing crisis. The findings underscore the importance of these specific financial metrics in evaluating bank stability during periods of extreme economic stress.