Solar photovoltaic (PV) is a dominant form of renewable energy source and has been widely deployed, but increasing PV power integrated into electric power grids creates challenges in the planning and operation of power grids due to PV power’s intermittency and variability nature. Accurate solar PV power generation prediction techniques are essential to overcome these challenges. This chapter proposes a short-term PV power generation prediction framework by using nineteen regression models within five regression families. To further enhance the forecasting model’s performance, hyperparameter optimization and tuning is discussed through the MATLAB Regression Learner toolbox. The historical datasets are utilized to develop the proposed forecasting models.