India, a rapidly growing economy with a population exceeding one billion, faces a significant demand for energy. Despite the increasing population, power generation in the country has also seen a rise. To address India’s escalating energy requirements, harnessing solar energy emerges as the most suitable solution, taking advantage of the country’s favorable geographical location. However, effectively utilizing the solar energy generated presents challenges. While organizations invest effort in generating solar energy, they often neglect the importance of utilizing it optimally. This oversight can result in financial losses for organizations, as they invest substantial amounts in setting up solar energy systems but fail to monitor their utilization. The main objective of this study is to analyze the usage of solar energy and predict the amount of energy that our institution, G. Narayanamma Institute of Technology and Sciences, would generate. The study uses four distinct algorithms, namely multiple linear regression, decision trees, gradient boost, and XGBoost. We have evaluated these algorithms and identified the most accurate model based on their performance.