Trade, services, and investment are the main pillars that are integrated in driving global economic growth. This study aims to analyze the “ability of the Altman Z-Score model to predict financial distress in companies in the Trade, Service & Investment (TSI) sector on the Indonesia Stock Exchange (IDX) for the period 2019–2023.” The method used is a quantitative approach with binary logistic regression analysis of the financial statements of 15 companies selected purposively. The results indicate that the Altman Z-Score can predict financial distress, although its accuracy is limited in complex market conditions. These findings imply the need for regular financial evaluations and the development of more adaptive predictive models to address the dynamic financial conditions of companies. Additionally, this study is expected to provide practical benefits for investors, creditors, and company management in anticipating bankruptcy risks while developing sustainable financial strategies.
Nurhayati et al. (Mon,) studied this question.