Rainfall predictionPrediction and crop yield estimation are critical agricultural planning and management factors. Climate change has an increasing impact on agricultureAgriculture's function in developing nations like India and many crops. Although there are several methods or techniques for calculating agricultural production, their precision is not up to pace. The literature study indicates that there are no appropriate treatments or technological advancements for the aforementioned issue. The over-mechanization of agricultureAgriculture was being pushed by this technique. The use of machine learningMachine learning techniques has demonstrated encouraging results in recent years in improving the accuracy of these forecasts. In order to forecast rainfall and estimate agricultural productivity, this study evaluates the efficacy of two machine learning algorithmsMachine learning algorithms. The implementation of the ridge classificationRidge classification technique and the K-Nearest Neighbors’ (KNN) classification algorithm reflects the complex relationship between rainfall patterns and agricultural yields. To improve the performance of the models, several feature engineeringFeature engineering and data pretreatment techniques are used.