In the era of rapid technological advancement, agriculture is undergoing a digital transformation. Our Crop Disease Detection and Recommendation System helps farmers identify crop diseases and provides recommendations for crop and fertilizer selection through three key services: Disease Detection, Crop Recommendation, and Fertilizer Recommendation. Using a Convolutional Neural Network (CNN) with a 96.69% accuracy, the system precisely identifies diseases in crops such as apple, corn, grape, potato, and tomato. Additionally, it employs machine learning algorithms, including Random Forest and Naive Bayes, to provide highly accurate crop recommendations (99.09%) based on soil and climate data. This system revolutionizes agricultural decision-making by offering actionable insights to enhance crop resilience, optimize resources, and promote sustainable farming.