Purpose: This study investigates how financial and entrepreneurial capability configurations differentiate internationalized from domestically oriented Thai SMEs. By adopting a decision‐science perspective, the study identifies the capability patterns that shape firms’ strategic international orientation. Design/methodology/approach: This research, which utilizes survey and financial data from 179 Thai SMEs (2021–2023), employs an inductive machine learning approach based on Extreme Gradient Boosting (XGBoost). The analytical framework integrates profitability, liquidity, leverage, operational efficiency, international experience, team readiness, market knowledge, and institutional connectivity. Feature importance scores and confirmatory statistical tests are used to validate differentiating capability structures. Findings: Internationalized SMEs demonstrate stronger financial agility, higher profitability, disciplined leverage, and superior resource utilization combined with entrepreneurial preparedness, as evidenced by international experience, risk tolerance, effective team coordination, and institutional embeddedness. In contrast, localized SMEs exhibit liquidity-heavy but low-dynamism profiles, limited network engagement, and weaker organizational readiness. The machine learning model highlights the non-linear interactions among these capabilities, achieving high predictive accuracy (92.59%). Practical implications: The findings offer a capability-based diagnostic tool for managers and policymakers. Strengthening financial agility, team readiness, and institutional ties can enhance the global competitiveness of SMEs. Originality/value: This study introduces a multidimensional, data-driven capability configuration model for SME internationalization, advancing decision science, dynamic capabilities, and network-based theories in emerging-market contexts.