The primary objective of this study was to construct a 3D Convolutional Neural Network (CNN) based on multimodal MRI, clinical and demographic data. The purpose was to effectively discriminate healthy controls and individuals diagnosed with Parkinson's Disease (PD) in advanced stages. Subsequently, the designed model was used to develop another CNN, mirroring the architecture of the previous one. This secondary CNN was developed to differentiate between controls and PD patients in earlier disease stages. The ultimate goal of this project was to design a CNN capable of predicting the progression of PD, classifying whether an individual's prognosis would remain stable or worsening.