Penelitian ini bertujuan untuk memprediksi kesulitan keuangan pada perusahaan non keuangan yang telah terdaftar di Bursa Efek Indonesia selama periode 2010 hingga 2019. Penelitian dilakukan dengan melihat pengaruh dari variabel financial ratio, pasar, dan ekonomi makro sebagai variabel independen terhadap kesulitan keuangan sebagai variabel dependen. Penelitian ini menggunakan model regresi logistic untuk melihat nilai koefisien diantara dua kelompok sampel yaitu perusahaan yang mengalami kesulitan keuangan dan perusahaan yang tidak dengan model regresi logit. Penentu perusahaan yang mengalami financial distress didasarkan pada Zmijewski X Score yang memiliki nilai positif. Temuan dalam penelitian menunjukkan model regresi variabel financial ratio, pasar, dan ekonomi makro berpengaruh signifikan dalam memprediksi kesulitan keuangan. Dari empat model regresi yang dilakukan, didapatkan hasil bahwa model yang menggunakan variabel financial ratio, market, dan macroeconomic, financial ratio dan macroeconomic serta financial ratio dan market yang memiliki nilai 90,6 %, sementara model yang menggunakan variabel market dan macroeconomic memiliki tingkat signifikansi 89,8 %.

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This study aims to predict financial difficulties in non-financial companies that have been listed on the Indonesia Stock Exchange during 2010 to 2019 period. The study was conducted by observing the influence of financial ratio, market and macroeconomic variables as independent variables and financial distress as the dependent variable. This study uses a logistic regression model to see the coefficient value between the two sample groups, namely companies experiencing financial distress and companies that are not by using a logit regression model. The determinants of companies experiencing financial distress are based on the Zmijewski X Score which has a positive value. The findings of this study indicate that the regression model of the financial ratio, market and macroeconomic variables has a significant effect in predicting financial distress. From the four regression models carried out, the results show that models that use financial ratio, market and macroeconomic, financial ratio and macroeconomic variables as well as financial ratios and markets variables have the highest level of significance with a value of 90.6%, while the model that uses market and macroeconomic variables has a significance level of 89.8%.