Plant diseases are a serious hazard to agriculture, harming the world’s food security and resulting in significant losses for farmers. In India, infections account for 35 percent of crop losses, therefore efficient disease identification is critical. Our research is focused on creating a strong Deep Learning Model for precise and timely identification of tomato leaf diseases in order to address this. By utilizing RCNN architectures like MobileNet and AlexNet, we hope to extract complex patterns from leaf photos. The ‘Plant Village Dataset’ from Kaggle is a thorough training and assessment set that guarantees the dependability of the model. Our study supports the pressing need for technical advancements to lessen the effects of plant.