The cultivation of rubber trees in Kerala is an important part of the agricultural sector, which in turn helps to boost the local economy and provide jobs. Accurate forecasting of rubber output is vital for successful resource management and informed decision-making in the rubber sector because of the volatility of rubber pricing and the impact of many factors on rubber production. For the purpose of forecasting rubber output in Kerala, this study compares the Auto Regressive Integrated Moving Average (ARIMA) and Seasonal Auto Regressive Integrated Moving Average (SARIMA) models. The study intends to evaluate the performance of both models in predicting rubber output by using historical data and taking into account a variety of seasonal and non-seasonal elements, providing useful insights into the best-suited technique for robust and accurate forecasting.