<![CDATA[This study aims to analyze the differences in financial distress prediction results using the Altman Z-Score, Springate, Zmijewski, and Grover models and to determine the most accurate model in predicting financial distress among pharmaceutical sub-sector companies listed on the Indonesia Stock Exchange during the 2020–2024 period. This research employed a quantitative approach with a descriptive-comparative design. Secondary data were obtained from the annual financial statements of 11 pharmaceutical companies selected through purposive sampling, resulting in 55 observations. Data analysis was conducted using descriptive statistics, the Kolmogorov–Smirnov normality test, the Kruskal–Wallis test, and accuracy testing by comparing prediction results with the actual financial condition of the companies. The results indicate a significant difference in financial distress predictions among the four models, as evidenced by the Kruskal–Wallis test with an Asymp. Sig. value of <0.001. Accuracy testing revealed that the Zmijewski model achieved the highest prediction accuracy (94.5%), followed by the Grover model (90.9%), Springate model (83.6%), and Altman Z-Score model (81.8%). The superior performance of the Zmijewski model is attributed to its emphasis on profitability, leverage, and liquidity ratios, which better represent the financial characteristics of pharmaceutical companies. Therefore, the Zmijewski model is recommended as the most appropriate financial distress prediction model for pharmaceutical sub-sector companies listed on the Indonesia Stock Exchange.]]>
