Despite the various intervention by the government and private bodies to help the agriculture sector, farmers in Nigeria still complain about poor productivity. Utilizing technology, research, and development to the fullest extent is necessary for sustainable agricultural practices. This study aims to demonstrate the advancement and accuracy of machine learning algorithms in predicting the best crop to be grown based on field data. The outcome of the various algorithms used resulted in high prediction, driving home the suitability of machine learning algorithms in improving agricultural practices and methods. Adopting precision farming will have an exponentially positive effect on crop growth and crop productivity, as farmers will make informed decisions thereby increasing the sustainability of the agricultural sector and ultimately strengthening the economy.