Nowadays, unpredictable climate change has led to poor yields of the crops affecting their performance and growth. Crop prediction performed in advance of the harvest, would help the farmers adopt appropriate measures, in terms of storage, etc. It will also be advantageous for the government, policymakers, etc. This project will help counsel the farmer in sowing reasonable crops by deploying machine learning techniques like Ensemble learning, one of the best technologies in crop prediction. Machine learning will help decide What to grow, what to do while the crops are in their growing season., after harvesting, etc. Factors like temperature, rainfall, area, etc. will be considered. Different Machine Learning (ML) algorithms will be applied in the research of crop classification. The classification results achieved by this system will largely help the farmers decide which crop to grow. The accuracy of ensemble classifications is 97.44 outperformed other machine learning classifiers.