Yielding to find the prediction is a critical issue for farmers and the agricultural domain. Farmers expect to know the yield of the crops they grow. Older farmers can easily predict when it will rain and when it will be necessary to cultivate in the agricultural field. Yield is simple, and it is determined by weather conditions, pest control, and harvesting plans. To increase production, more pesticides, herbicides, and fertilizers were traditionally applied, which had a greater environmental impact. Accurate information that makes crop history more yielding is the main reason for making the decision, and in particular it makes risking a high factor and their risk management. This paper presents a crop yield prediction system, which helps the farmers to predict the crop yield. An ANN is developed to obtain the data from pH sensor and moisture sensor, wherein this data values are trained and tested and also it has been used to predict the crop yielding in the particular field. Experimental results show the result of ANN algorithm with an accuracy of 86%. © 2022 Elsevier B.V., All rights reserved.