In the process of providing credit, banks are faced with the risk of bad debts, where the borrower is unable or unwilling to repay the loan that has been granted. This risk can be caused by economic factors such as slowing growth, market instability, or a financial crisis. In addition, internal factors such as imprudent credit policies, poor risk management, or the bank's inability to conduct effective monitoring can also contribute to bad debt risk. This study aims to analyze the effect of capital adequacy ratio, return on assets, loan-to-deposit ratio and operating expenses on non-performing loans in conventional banks. The type of research used is quantitative with a cross-sectional approach. The number of conventional banks sampled was 20, with an observation period of 2021–2022, using quarterly data. The data analysis technique uses multiple linear regression analysis using three alternative regression models, namely the common effect model (CEM), fixed effect model (FEM), and random effect model (REM). The application used for testing is e-Views 12. Hypothesis testing is done with the t test. The results showed that the final model chosen was the REM) The panel data regression model on the percentage of NPL data estimated with the REM is shown in the equation. NPL = 1.139 - 0.028*CAR - 0.002*ROA + 0.012*LDR + 0.018*BOPO. CAR variables have a negative and significant effect on NPL; ROA has a negative and significant effect on NPL; and LDR has a positive and significant effect on NPL. BOPO has a negative and significant effect on NPL.