Computational Thinking (CT) has become an essential 21st-century competence that needs to be integrated into mathematics education to enhance students’ problem-solving and analytical skills. However, conventional mathematics instruction often fails to systematically develop decomposition, abstraction, pattern recognition, and algorithmic thinking. This study aims to examine the effectiveness of Project-Based Learning (PjBL) in developing students’ computational thinking in mathematics. A quasi-experimental design with a pretest–posttest control group was employed involving two junior secondary school classes. The experimental group received mathematics instruction through Project-Based Learning, while the control group experienced conventional teaching. Data were collected using a computational thinking test, a conceptual understanding test, and a student engagement questionnaire. The data were analyzed using descriptive statistics, paired and independent samples t-tests, and effect size calculations. The results indicate that students in the PjBL group achieved significantly higher improvements in computational thinking skills compared to the control group, with large effect sizes observed particularly in decomposition, pattern recognition, and abstraction. Algorithmic thinking also improved with structured scaffolding. The study concludes that Project-Based Learning provides an effective instructional framework for fostering computational thinking and enhancing conceptual understanding in mathematics education.