Abstract: This project introduces an AI-powered agricultural management system designed to support farmers with data-driven insights. The system features crop yield prediction using a Random Forest Regressor, considering key factors like rainfall, temperature, humidity, and soil properties. A crop recommendation module, built with a Random Forest Classifier, suggests the most suitable crops based on regional and climatic conditions. Additionally, a chatbot, powered by TF-IDF and cosine similarity techniques, provides quick responses to common agricultural questions on crop selection, fertilizer usage, and disease management. The inclusion of a weather API offers real-time weather updates, enabling farmers to stay informed about current environmental conditions. Deployed as a web application, the platform combines multiple tools into one accessible interface, aiming to improve farm productivity, enhance decision-making, and promote modern agricultural practices. This system aims to improve agricultural decision-making, enhance farm productivity, and support sustainable farming.

Keywords: Agricultural Decision Support, Crop Yield Forecasting, Crop Recommendation, AI in Farming, Machine Learning, Chatbot Integration, Weather Data, Smart Agriculture.

| DOI: 10.17148/IARJSET.2025.12302