This study conducts a meta-analysis of 219 empirical articles from Web of Science, Scopus, and Engineer Village to investigate the factors influencing learners' continuance intention toward online education platforms. The analysis integrates variables from the expectation-confirmation model, information system success model, theory of planned behavior, and flow theory. Key findings include strong correlations between attitude (r=0.603), perceived usefulness (r=0.526), and satisfaction (r=0.606) with continuance intention. The study aims to provide valuable insights for educators, policymakers, and platform developers, offering scientific guidelines to enhance the effectiveness and attractiveness of online education platforms. The research questions focus on identifying the theoretical foundations and specific variables that influence continuance intention, as well as determining the key variables with significant effects. The study's findings are intended to support the continuous improvement of online education platforms and ensure high-quality learning experiences for learners.This study conducts a meta-analysis of 219 empirical articles from Web of Science, Scopus, and Engineer Village to investigate the factors influencing learners' continuance intention toward online education platforms. The analysis integrates variables from the expectation-confirmation model, information system success model, theory of planned behavior, and flow theory. Key findings include strong correlations between attitude (r=0.603), perceived usefulness (r=0.526), and satisfaction (r=0.606) with continuance intention. The study aims to provide valuable insights for educators, policymakers, and platform developers, offering scientific guidelines to enhance the effectiveness and attractiveness of online education platforms. The research questions focus on identifying the theoretical foundations and specific variables that influence continuance intention, as well as determining the key variables with significant effects. The study's findings are intended to support the continuous improvement of online education platforms and ensure high-quality learning experiences for learners.