<![CDATA[This study aims to analyze differences in financial distress prediction results generated by the Altman, Springate, and Zmijewski models and to determine which model yields the highest accuracy for non-cyclical consumer sector companies listed on the Indonesia Stock Exchange during the 2022–2024 period. The study employs a descriptive-comparative quantitative approach using secondary data derived from corporate financial statements. A purposive sampling method was used, resulting in a sample of 70 companies, yielding 210 observations over the three-year period. Analysis was conducted using descriptive statistics, the Kruskal-Wallis test, and model accuracy testing. The Kruskal-Wallis test results yielded an H-value of 403.470 with a significance level of < 0.001, indicating significant differences in the prediction results among the three models. Accuracy test results revealed that the Altman model achieved 37.62% accuracy, the Springate model 80.00%, and the Zmijewski model 89.52%. Consequently, the Zmijewski model demonstrated the highest accuracy and the lowest error rate. These findings suggest that the selection of a prediction model should take into account sector characteristics and the specific ratio components employed; furthermore, the results provide valuable information for companies, investors, and stakeholders regarding the early detection of financial distress. ]]>
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