This research aims to find out and analyze conditions financial distress in mining sector companies listed on the Stock Exchange Indonesia for the 2019-2023 period using the Altman Z prediction model Score, Springate, Zmijewski and Grover. The sample companies are: used in this research were 33 companies obtained by purposive sampling and observations for 5 years to obtain the sample size into 165 samples. The type of data used is secondary data, meanwhile data retrieval techniques obtained from historical data of mining companies, financial reports published by the Indonesian Stock Exchange and literature studies. Technique The data analysis used is a parametric statistical test, namely the Paired Sample test t-test and test the accuracy of the prediction model with the condition that the data must be distributed normal. The results of this study show significant differences between Altman, Springate, Zmijewski, and Grover models in predicting financial distress, and the highest level of accuracy achieved by the Zmijewski model with level accuracy of 94%
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