Since a long years, agriculture is considered as a major profession for livelihoods of the Indians. Still, agriculture is not profitable as many farmers take the worse step as they cannot survive from the burden of loans. So, one such place where there is yet large scope to develop is agriculture. In comparison with other countries, India has the highest production rate in agriculture. However, still, most agricultural fields are underdeveloped due to the lack of deployment of ecosystem control technologies. Agriculture when combined with technology can bring the finest results. Crop yield depends on multiple climatic conditions such as air temperature, soil temperature, humidity, and soil moisture. In general, farmers depend on self-monitoring and experience for harvesting fields. Scarcity of water is a main issue in today’s life. This scarcity is affecting people worldwide. So water is also a vital component of crop yield, here we are considering rainfall instead direct water. Predicting the crop selection/yield in advance of its harvest would help the policymakers and farmers for taking appropriate measures for farming, marketing, and storage. Thus, in this paper we propose a crop selection using machine learning technique as support vector machine (SVM) and polynomial regression. This model will help the farmers to know the yield of their crop before cultivating the agricultural field and thus help them to make the appropriate decisions. It attempts to solve the issue by building a prototype of an interactive prediction system. Accurate yield prediction is required to be done after understanding the functional relationship between yield and these parameters because along with all advances in the machines and technologies used in farming, useful and accurate information about different matters also plays a significant role in it. In this paper, we have simulated SVM and polynomial regression technique to predict which crop can yield better profit. Both of the models are simulated comprehensively on the Indian dataset, and an analytical report has been presented.