In spite of efforts to combat it, malaria in India continues to be a major threat to public health. Future trends in Malaria-related mortality in India were predicted using the Autoregressive Integrated Moving Average (ARIMA) model. We ran crucial diagnostic tests, including the Augmented Dickey-Fuller (ADF) test, the Autocorrelation Function (ACF), the Partial Autocorrelation Function (PACF), and the Box- Jenkins approach, to make sure the model was accurate. The stationarity of the time series data and the optimal ARIMA model parameters could then be determined with the use of these tests. We were able to build a reliable forecasting model that sheds light on the future of Malaria-related mortality in India by combining various analytical tools. This study's findings will help in the development of preventative strategies and focused treatments to lessen the impact of Malaria in the country.