Scientists clash over how globalization affects the environment, particularly forests. To fill this gap, we analyzed the impact of aggregated (globalization index as a whole) and disaggregated (economic, commercial, social, and political) globalization on forest conversion in 23 countries covering tropical forests in the Amazon Basin, Congo Basin, and Southeast Asia from 2000 to 2020. To achieve this, we used the GMM model and the sequential (two-step) estimation of the two-step GMM estimator of the linear panel data (SELPDM) as a robust test. According to the results of these econometric methodologies, a 1% increase in globalization (economic, commercial, social, and political globalization) will reduce forest conversion by 0.012 (0.011, 0.06, 0.04, 0.09) respectively, and a 1% increase in biomass and agricultural land. Population density and grain production will increase forest conversion by 0.059, 0.084, 0.038, 0.029, ceteris paribus. Furthermore, the findings support the N-shaped EKCd hypothesis between economic performance and forest conversion, and all these results were confirmed by SELPDM used as the robustness test. As a result, we proposed promoting more environmentally friendly forms of globalization, aiming for sustainable development without sacrificing ecosystem protection, and energy efficiency, particularly with the help of new environmentally friendly technologies, paving the way for even stronger economic growth and improved educational attainment in tandem with improved agricultural.