An autoregressive integrated moving average (ARIMA) model is useful to analyze time-series data either for better understanding or for forecasting future points in the series. This paper aims to model and forecast the GDP of Sri Lanka based on the Box-Jenkins approach based on the annual data from 1971 to 2021. Box ? Jenkins technique is a relatively advanced time series forecast method it is applied in this paper to forecast GDP at the million US$ in Sri Lanka. The study attempt to study and model to forecast the GDP of Sri Lanka using an appropriate forecasting model. After testing the stationarity of the data, the series were stationary at the first difference after calculating the logarithm of the data. From the Correlogram of ACF, we determined the appropriate ARIMA model which is ARIMA (1,1,1) to forecast GDP. The ARIMA (1, 1, 1) model was seen as a superior fit model for estimating Sri Lanka?s GDP at a million US$. According to the values predicted, Sri Lankan GDP shows a higher growth trend in the next few years from 2022 to 2030 at million US$. However, the forecasting result of this model is only a predicted value.