<![CDATA[Capstone courses in software engineering require students to integrate knowledge and skills acquired from multiple prerequisite courses. However, not all prerequisite courses contribute equally to student success in capstone projects. This study investigates the contribution of individual programming and database courses to student performance in a software development capstone course using Multiple Linear Regression (MLR). Academic records from 482 undergraduate students were analyzed, including grades from prerequisite programming and database courses, with Grade Point Average (GPA) included as a control variable. Ordinary Least Squares (OLS) was used to estimate the regression model, while LASSO regression and partial correlation analysis were applied as supporting analyses to assess robustness and interpret direct relationships. The results indicate that Data Structures, Object-Oriented Programming, Web Programming, Software Project Management, and Platform-Based Programming have a significant positive contribution to capstone performance. In contrast, introductory courses show mainly indirect effects. Database Systems exhibits a reduced unique contribution after controlling for other courses, suggesting that its impact is embedded within broader development skills. These findings demonstrate that course-level academic data can provide actionable insights for curriculum evaluation and support data-driven improvements in capstone preparation.]]>
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