In the traditional agriculture in India, the farmers are not able to make profit from their crops. We propose a price prediction model using Machine Learning approaches, which helps the farmers to make appropriate decisions well before cultivation and later on selling their farm outputs. We have chosen cardamom as a case study in which the data being collected over four decades’ monthly average prices. We propose an ensemble method of multivariate linear regression model and ARIMA model over the clustered average monthly cardamom prices across forty years. The robustness of the proposed model is evaluated against four-decade monthly price movement.