The increasing incorporation of solar power into modern power grids demands accurate models for the prediction of solar power output and solar radiation. In this paper, Solar Intelligence is introduced, a prediction system based on machine learning-based models to forecast the accuracy of these predictions. This model has the ability to utilize past solar radiation data, weather forecasts, and environmental conditions to predict solar power output with precision. The application of this system allows grid operators and energy stakeholders to maximize energy generation, enhance grid stability, and ensure a smooth integration of renewable energy. The system also has the capability to propel substantial solar energy management improvements, enabling utilities and consumers to make better-informed decisions and achieve optimal solar energy utilization efficiency.