Agriculture is important for India. Plant diseases pose significant threats to global food security, leading to substantialcrop yield losses. Early and accurate disease detection is crucial for timely intervention and effective management. This paperpresents a novel mobile-based system that leverages advanced deep learning techniques to diagnose and predict plant leaf diseases.The system utilizes a Convolutional Neural Network (CNN) model trained on a large dataset of images capturing various plantdiseases. Users can capture images of diseased leaves using their mobile devices and upload them to the system. The CNN modelanalyzes the images, identifies the specific disease, and provides a detailed diagnosis along with recommended treatment options. Byempowering farmers with real-time disease information, this system aims to enhance agricultural productivity and sustainability.Plant diseases remain a significant challenge in agriculture, causing substantial crop yield losses and economic burdens. Early andaccurate disease diagnosis is critical for timely intervention and effective management strategies. This research presents a mobilebased system that integrates advanced deep learning techniques to automatically detect and predict plant leaf diseases.The systemleverages a Convolutional Neural Network (CNN) model, specifically designed to extract relevant features from images of diseasedleaves. The CNN model is trained on a diverse dataset comprising imag of various plant species and their associated diseases. Byanalyzing the input images, the model can accurately classify the disease and provide a detailed diagnosis. To enhance useraccessibility and convenience, the system is implemented as a mobile application. Farmers can capture images of affected leavesusing their smartphones and upload them to the application. The system processes the images, performs disease detection andprediction, and presents the results in an easy-to-understand format. Additionally, the application provides recommendations forsuitable treatments, such as specific pesticides or fungicides, to mitigate the impact of the disease. By empowering farmers withtimely and accurate disease information, this mobile-based system aims to improve agricultural practices, reduce crop losses, andcontribute to sustainable agriculture.JEL Classification Number: I10, C88, L86.