Abstract
Small and medium-sized enterprises (SMEs) play a critical role in economic development; however, many SMEs continue to face financial instability despite increased access to external financing and microfinance support. This study examines the influence of operational financial indicators on SME financial sustainability using secondary operational financial data. Specifically, the study investigates the effects of revenue, accounts receivable days, inventory days, loan balance, and owner injections on SME financial stress. A quantitative explanatory research design was employed using a secondary dataset consisting of 1,600 SME observations obtained from Kaggle for the period 2024–2025. Descriptive statistics, correlation analysis, logistic regression, and machine learning techniques, including Random Forest classification with SMOTE balancing, were applied to analyze the data. The findings reveal that inventory days significantly increase SME financial stress, indicating that inefficient inventory management weakens liquidity and operational sustainability. Accounts receivable days also demonstrated a moderate positive relationship with financial stress, while revenue, loan balance, and owner injections did not show statistically significant effects in the regression analysis. Furthermore, the predictive model demonstrated limited classification capability, suggesting that SME sustainability is influenced by broader operational and managerial factors beyond financial indicators alone. The study contributes to SME sustainability literature by integrating operational financial analysis with predictive analytics and provides practical implications for SME financial management and policy development.