This paper presents a system for predicting the wind speed and profit of wind turbines using integration technologies, along with the applications of machine learning. The system utilizes data on wind speed and energy production to accurately estimate future profit of wind farms. The implementation includes methods of data collection, analysis, and the use of random forest algorithm, enabling users to forecast production efficiency. The paper contributes to the development of innovative solutions for monitoring and assessing renewable resources, facilitating the transition to a more sustainable energy future