This study presents a comprehensive analysis of global sustainable energy trends using statistical techniques and machine learning methods. The research evaluates long-term patterns in renewable energy consumption, fossil fuel dependence, and the transition toward low-carbon systems from 1990 to 2022. Using a CRISP-DM data-science framework, the study performs data preparation, exploratory analysis, correlation assessments, regression modelling, and predictive analytics to understand the future trajectory of clean…