The focus of the project lies in predicting agricultural crop production in India, a critical aspect of farming that empowers farmers to make well-informed decisions about their crops. This prediction process entails estimating the quantity of crops expected to be harvested in a specific area, drawing upon factors such as soil composition, weather patterns, and agricultural management techniques. In recent times, machine learning (ML) has emerged as a pivotal tool for such predictions. ML, a subset of artificial intelligence (AI), enables computers to learn from data patterns without explicit programming. This characteristic renders ML particularly effective for crop yield prediction, as it can discern intricate relationships within vast datasets and generate predictions based on these discerned patterns.