This document discusses using machine learning techniques to predict crop yields. It begins with an abstract that outlines the importance of agriculture and maintaining crop production in India. The objectives are then stated as empowering farmers with knowledge of different crops and climate changes and overcoming obstacles by applying machine learning to predict crop yield based on factors like temperature, rainfall, and area. Related work on using climate data and machine learning algorithms like SVM and regression to predict yields is reviewed. The proposed system aims to select optimal crops for a land plot using techniques like XGBoost, Naive Bayes and SVM based on environmental variables. It is concluded that opportunities remain to enhance outcomes by considering all variables simultaneously and using larger datasets.