This chapter shows the ways to implement statistical prediction. The starting point for statistical time series forecasting is ARIMA, we introduce the automatic order selection function auto.arima(), a routine offered by package forecast. Besides ARIMA, this chapter also includes several nonlinear time series models, for example, self-exciting threshold autoregression. We also detail the procedure to generate multistep forecasts and onestep ahead forecast.