<![CDATA[Financial distress is a condition that needs to be detected early because it can increase the risk of delisting and reduce investor confidence. Raw materials companies are characterized by high capital requirements, making them more vulnerable to financial stress. This study aims to analyze the financial distress conditions of raw materials companies at risk of delisting on the Indonesia Stock Exchange and compare the accuracy levels of the Altman Z-Score, Zmijewski, and Springate methods. This study uses a quantitative approach with descriptive methods. The study population consisted of 13 raw materials companies with the potential for delisting, while the sample was determined using a purposive sampling technique, resulting in five companies for the 2020-2024 period. The research data consisted of secondary financial reports collected through documentation techniques and literature studies. Data analysis was performed using the Altman Z-Score, Zmijewski, and Springate models, along with calculations of accuracy and error type. The results show that the Altman Z-Score method classified three companies as experiencing financial distress, the Zmijewski method produced a more dynamic classification, while the Springate method identified almost all companies as experiencing financial distress. The research conclusion shows that the Altman Z-Score method has the highest average accuracy rate of 80%, making it the most suitable method for detecting financial distress in raw material sector companies at risk of delisting]]>
