<![CDATA[In business and commercial activities, risks are inevitable, particularly the risk of bankruptcy. This risk is especially critical in the banking sector, which functions as a financial intermediary that collects funds from third parties (investors), including the public, companies, and government or private institutions, and redistributes these funds to parties in need of financing. Banks also engage in investment activities such as real estate and other sectors. Consequently, banks face potential risks in both the short and long term, particularly the risk of bankruptcy. Bankruptcy risk may arise from various factors, both internal and external. This risk applies to all sectors, whether managed by the government or private entities. In the private sector, indications of bankruptcy risk can significantly affect investor confidence in investing in bank shares, while the public may also become reluctant to deposit funds in such banks. Therefore, it is important to detect and minimize bankruptcy risk by analyzing financial conditions using bankruptcy prediction models such as the Altman Z-Score, Springate, and Zmijewski X-Score, as well as by examining the influence of CAMEL-based financial performance on these three models. This study employs a quantitative research approach using secondary data obtained from the financial statements of the sampled banks. The analysis aims to identify bankruptcy risk indicators in bank financial reports through the calculation of bankruptcy scores and multiple linear regression analysis. The results of the study indicate that CAMEL performance has a significant effect on the indication of bankruptcy risk, although the level of significance varies across banks and prediction models. These findings provide valuable evaluations and contributions for bank management and investors, and also offer theoretical and practical insights for academics conducting further research or collaborative studies to develop new scholarly work.]]>
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