Agriculture plays a huge role in India. It keeps a ton of people employed and pumps a lot into the economy. Still, farmersruninto all sorts of issues. They struggle with picking the right crops. Optimizing fertilizers is another headache. And spottingdiseasesearlyin crops. All that leads to lower yields and worn-out soil. This study brings in an AI setup that pulls together crop suggestions, betterfertilizer use, and disease spotting all in one package. It looks at soil stuff like nitrogen levels, phosphorus, potassium, pHbalance,andhow moist the ground is. Then it factors in things like the weather, temperature, rainfall too. From there, it suggests thebest cropandfertilizer mix. Machine learning handles the predictions for crops and fertilizers pretty accurately. For diseases, it uses deeplearningwiththese CNN models to check leaf pictures and classify problems. The whole thing is meant to help farmers, whether theyareprosorjuststarting out. They can make smarter choices based on data. That boosts yields, cuts down on wasted fertilizer, and keeps diseaselossesincheck. Overall, this AI way of doing things pushes agriculture toward being smarter, more sustainable, with tech right inthemix. Keywords—Artificial Intelligence, Machine Learning, Crop Recommendation, Disease Detection, Convolutional Neural Network.