This chapter reviews the panel data forecasting literature. Starting with simple forecasts based on fixed and random effects panel data models. Next, these forecasts are extended to allow for various ARMA type structure on the disturbances, as well as spatial autoregressive and moving average type disturbances. These forecasting methods are then studied in the context of seemingly unrelated regressions. We highlight several forecasting empirical applications using panel data, as well as several Monte Carlo studies that compare various forecasting methods using panel data. The chapter concludes with suggestions for further work in this area.