This study aims to analyze the financial distress conditions and compare the accuracy levels of the Springate, Grover and Fulmer models at PT Smartfren Telecom Tbk during the 2020–2024 period. The research methodology used is descriptive quantitative with secondary data in the form of the company's annual financial reports. The analysis method is carried out by applying financial ratios to the bankruptcy prediction model formula and comparing the results with the company's actual conditions to assess the level of prediction accuracy. The findings indicate that company needs to control the use of debt in financing investments, as well as increase the effectiveness of investment asset utilization in order to generate sustainable income and profits. Then based on the prediction results, the Springate and Fulmer models consistently classify companies in financial distress conditions in the 2020-2024 period, while the Grover model shows a grey area category in 2023. So in terms of accuracy levels, the Springate and Fulmer models have a higher accuracy level of 80% compared to the Grover model with an accuracy level of only 60%. These findings indicate that the Springate and Fulmer models are more reliable for use as an early warning system in detecting potential financial distress in telecommunications sector companies.
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