Agriculture is the largest livelihood provider in India. It contributes a significant figure to the gross domestic product. However, crop diseases can significantly impact agricultural productivity and food security. Accurate and timely classification of diseases in plants or crops is essential for effective disease management. These facts encourage our team to work upon the SDG:2 “End hunger, achieve food security and improved nutrition and promote sustainable agriculture.” After our research the team came into conclusion to do “Peach Leaf Disease Classification.” The literature survey concluded into using convolutional neural network. Machine learning models are increasingly used to identify and categorize plant diseases. Therefore, our team distributed among themselves four different architectures. Sequential CNN gave 96% accuracy, ResNet-50 gave 99.62% accuracy, VGG gave 97.50% accuracy, and AlexNet gave 99.25% accuracy. Our team is willing to focus on developing deep learning models capable of accurately distinguishing and classifying a diverse range of subcategories within broader classes.