This research paper presents a groundbreaking approach in economic forecasting by leveraging machine learning (ML) to predict GDP per capita. The study constructs a comprehensive ML model that integrates an array of critical energy-related and economic factors, such as access to electricity, usage of clean fuels, renewable energy capacities, and financial dynamics in the energy sector. This model aims to elucidate the complex relationships between these factors and GDP per capita, offering a nuanced understanding of how energy market variables impact a nation's economic health. In a novel application of this model, an interactive web application is developed. This digital platform enables users to input specific country data and the desired year to receive immediate, data-driven GDP per capita predictions, thus providing a valuable tool for policymakers, economic analysts, and industry experts.