Agriculture is very important for India, making up a big part (17–18%) of the country’s economy. Many people rely on farming for their livelihood. India has a lot of farmland, even more than the U.S. and China. But keeping crops safe from pests and diseases is crucial for getting good amount of produce. The research focuses on using technology like image processing and machine learning to help with this. Specifically, we looked at potato plants and their leaves. The model uses convolutional neural network (CNN) and got really good results. Our model could tell with 99.78% accuracy if a potato leaf was healthy or had diseases like early blight or late blight. The cool thing about our research is that it’s not just for the lab—it can be super helpful for farmers with big fields. The technology we used can quickly check large areas of farmland for any issues. This means we can find and deal with problems early, keeping crops healthy. Using technology like image processing, machine learning, and deep learning makes it easier and more accurate to identify diseases. This is a big deal for farmers with large farms, as it helps them keep an eye on everything without spending too much time. Our research is like giving a boost to India’s farming strength. The high accuracy of the model and its ability to measure the affected leaf area are big steps forward in making farming more precise. As India stays on top in global farming, adopting these advanced technologies is crucial for making sure the future of agriculture is strong and sustainable.