The main cause for the Parkinson’s Disease is Neurodegenerative brain disorder. The process of impairment of brain cells is called neurodegeneration. Generally, Parkinson’s Disease is diagnosed by clinical diagnosis method. Existing clinical methods are difficult for early diagnosing of Parkinson’s Disease through Invasive or Non-Invasive method. Artificial Neural Network provides a way to differentiate and diagnose the Parkinson’s Disease. Artificial Neural Network method helps people to diagnose Parkinson’s Disease earlier and saves their lives. This proposed method proves to be better for early identification of disease. This method uses Feed Forward Back Propagation and trainlm function for producing more accuracy. Among the comparative classifications, four are chosen for highest accuracy. This method found to be best for early deduction of the disease with result accuracy of 98.53 and 99.44 percent training and testing respectively.