This study examines the effects of the Russia-Ukraine war on the financial status of Russian and Ukrainian companies and determines the key factors influencing financial distress. The war in Ukraine has significant global implications, causing casualties and disrupting trade. This disruption affects vital goods like wheat, fertilizers, oil, and gas, and leads to inflationary pressures. While most countries report positive GDP growth in 2022, Russia and Ukraine are exceptions, with Ukraine experiencing a severe GDP decline. Artificial neural networks (ANNs) are used to create financial distress prediction models on a dataset comprised of 38 Russian and Ukrainian publicly traded companies listed on their respective stock exchanges. The study includes a panel dataset consisting of publicly listed Russian and Ukrainian companies used to construct a machine learning model in order to ascertain the war’s impact on corporate financial health. The ANN model had an overall classification accuracy of 90.6% and an area under the ROC curve of 95.1%. The three most significant financial distress predictors were found to be return on assets, debt-to-capital, and debt-to-equity ratios.