This study aims to evaluate the effect of global energy transformation and systematic energy change on climate change. The model is constructed from dynamic panel data which comprises 26 world regions from the World Database Indicators (WDIs), International Energy Atomic (IEA), and International Monetary Fund (IMF), with a span from 2005 to 2022. The Generalized system Method of Moment (sys-GMM) and pooled OLS and random effect models have been used to empirically evaluate the linked effect of global transformation and systematic change on climate change. The sys-GMM approach is used to control the endogeneity of the lagged dependent variable when there is an association between the exogenous variable and the error term. Furthermore, it omits variable bias, measurement errors in the estimation, and unobserved panel heterogeneity. The econometric applications allow us to quantify the direct effect of global transformation and systematic change on climate change. The empirical analysis revealed that renewable energy, alternative energy, technology and innovation, and financial climate have a negative effect on climate change. It means that increasing consumption of the transformation energies leads to reducing the effect of climate change. However, fossil energy is statistically significant and positively affects climate change. Increasing the consumption of fossil energy raises the effect of climate change. There is a global need for massive decarbonization infrastructure that will help minimize the global warming that leads to climate change. Policies that take an endogenous approach through global transformation and systematic change should be implemented to reduce the effect of climate change. The policy should reduce the consumption of non-renewable energy and increase the consumption of renewable energy.