Rainfall is the main source of income for the majority of our country's economy. Agriculture is considered as the key source of income for the economy. A good estimate of rainfall is required to make proper agricultural investments. Rainfall forecasting is required for individuals living in coastal areas, in addition to agriculture. People living near the seaside are at a higher danger of heavy rain and flooding, therefore they should be aware of the weather forecast far in advance so that they can plan their stay accordingly. The prediction helps people in taking preventative steps, and it should also be accurate. Rainfall forecasting accuracy is important for countries like India, whose economy is heavily dependent on agriculture. To predict rainfall, a variety of machine learning models are used, including Multiple Linear Regression, Neural networks, K-means, Nave Bayes, and others. By extracting, training, and testing data sets and identifying and predicting rainfall, these systems accomplish one of these applications.