This scientific article provides an in-depth analysis of issues related to the financial stability of insurance companies and the early identification of bankruptcy risk. The study examines both classical and modern economic and mathematical models aimed at predicting bankruptcy, including the Altman Z-score, Lis, Taffler, Springate, and Zmijewski models, and evaluates their applicability to the insurance sector. In addition, approaches based on financial ratios, statistical methods, and machine learning techniques are comparatively analyzed. The research findings demonstrate the necessity of implementing an integrated bankruptcy forecasting system in insurance companies to enhance financial risk management.