Development of a Deep Learning model based on the U-Net architecture to automatically segment brain tumors from MRI scans. The model was trained on the LGG MRI Segmentation dataset and achieved a Dice Score of 85.8% and an IoU of 75.2%. A Streamlit web application allows users to upload an MRI scan and automatically obtain the predicted tumor segmentation mask.