Electricity is essential for the well-being of the human population. However, it is mostly generated via polluting, carbon-emitting traditional sources. To address these concerns, the world’s attention is shifting towards renewable energy sources that provide an infinite supply, are environmental friendly, and convert directly to electrical energy. Out of these renewable energy sources, solar energy is widely available, essentially unlimited, cost-effective, and efficient. The study presented a detailed and systematic review of PV output power forecast models. For creating an effective PV power prediction model, many steps are explored in the forecasting process, such as forecasting horizon, input data selection, pre-processing and post-processing of data, and different forecasting models. A critical analysis of various forecasting models, spanning from machine learning to physical models, is also offered. Furthermore, the probable advantages of hybrid approaches for PV power prediction models are comprehensively examined.