Comparative study of deep learning architectures (ResNet50, VGG16, and custom CNN) for plant disease classification across 38 different classes. Implemented and evaluated models on a comprehensive plant disease dataset, achieving state-of-the-art accuracy in disease detection and classification. Documentation available in the project repository.