This chapter discusses the development of a model for early detection of Parkinson's disease using artificial intelligence and machine learning techniques. The model, developed using the XGBoost algorithm, achieved an accuracy rate of 94.87%. The chapter highlights how the model performs well on new datasets, maintaining high accuracy. The potential applications of this technology in the healthcare sector and the importance of early diagnosis are emphasized, demonstrating its critical role in improving patient outcomes and enhancing the effectiveness of treatment strategies.