The relationship between computational thinking (CT) and academic self-efficacy for building students' academic resilience--a trait crucial for problem-solving, peer relationships, and confidence development--was investigated. A mixed-methods approach was employed in a study involving 60 participants; half were given CT instruction and half were instructed traditionally. Quantitative data were analyzed using analysis of covariance and path analysis, while MAXQDA software was employed for qualitative interview data. The study found a positive correlation between CT instruction and academic self-efficacy with increased academic resilience, particularly in the experimental group, and identified key factors contributing to resilience. This study demonstrates the effectiveness of computational thinking (CT) and academic self-efficacy in enhancing academic performance, offering a new understanding of how these elements can be integrated into education to boost student resilience. It establishes a direct empirical link between CT instruction and increased academic self-efficacy, underscoring the value of specific teaching methodologies in fostering resilience. The findings are significant for educators, policymakers, and stakeholders in developing strategies to enhance students' academic and personal success, thereby promoting their overall well-being. Recognizing the importance of CT and self-efficacy paves the way for customized educational programs that effectively support and empower students to thrive.