Drones are becoming increasingly important in our society. They are used for different purposes ranging from search and rescue to package delivery and entertainment. Reliability is an important aspect to consider for these real-world applications. One of the most significant challenges to drone stability and control is wind disturbances, which can affect flight accuracy, safety, and efficiency. Conventional control systems are often incapable of adapting to such external forces, leading to the risk of collisions and even system failures. This research aims to enhance the stability and robustness of the control system by integrating the traditional Model Predictive Control (MPC) algorithm with Gaussian Processes for real-time online wind predictions.