Wind power prediction involves applying state-of-the-art algorithms to the field of wind power generation so that wind power generation can be better connected to the electricity grid, and key technologies have developed rapidly. We rely on its wind and solar forecasts for over 500 plants (1,100+ MW), enhancing intraday and day-ahead energy management, cutting costs, and optimizing our trading yields. The Meteomatics Weather API is unique in the market as it provides flexible and fast access to a huge amount of weather data. A thorough analysis of machine learning (ML) techniques for wind power prediction is presented in this research, encompassing advancements from 2006 to 2025. Physical, statistical, traditional machine learning, deep learning, ensemble, and hybrid models are the categories into which current. Wind energy is one of the most significant and rapidly growing renewable energy sources worldwide. However, availability of wind resource is highly dependent on variable factors such as weather and local geographies, making wind power.