This study looks into the trends and future projections of mortality in South Africa that are caused by cardiovascular disease. An ARIMA model was utilized in order to do the analysis on the time series data pertaining to cardiovascular mortality. A number of diagnostic procedures, such as the Augmented Dickey-Fuller test and the Box-Jenkins analysis, were carried out to ascertain whether or not the data were stationary and to evaluate whether or not the model was adequate. This was done in order to guarantee the model's accuracy. The ACF and PACF were analyzed in order to recognize potentially seasonal and non-seasonal trends, and the ARIMA model that provided the greatest match was identified by applying the AIC criterion to the results. The findings of the forecasting study provide insights into the future trends of cardiovascular fatalities in South Africa. This, in turn, facilitates improved understanding and planning for public health interventions and policies to address this crucial issue.