Abstract: As one of the strongest atmospheric circulations during boreal winter, the East Asian winter monsoon (EAWM) dominates the East Asia winter climate. Therefore, it is of great significance to carry out research on the seasonal prediction and predictability of the EAWM. In this study, the prediction performance of the East Asian winter monsoon (EAWM) is assessed using the seasonal hindcast data (1993–2016) from the German Climate Forecast System (GCFS2). The main features of the EAWM, including the Siberian High (SH), East Asian trough, East Asian jet stream, and surface air temperature and precipitation over East Asia, are predicted well using GCFS2. The interannual variations of the East Asian trough and surface air temperature are skillfully predicted by GCFS2, along with the EAWM index (EAWMI), which is defined by the sea level pressure. Moreover, the EAWM-related atmospheric circulation, surface air temperature, and precipitation anomalies over oceans are well predicted. The good EAWM prediction skills of GCFS2 are mainly ascribed to the successful reproduction of the EAWM–El Niño southern oscillation (ENSO) relationship and ENSO teleconnection. The correlation coefficient between the EAWM and ENSO is −0.46 (1993–2016), which is higher than the observed value. This indicates that the enhanced EAWM–ENSO relationship in GCFS2 is a useful parameter in predicting EAWM at two months leading or longer. The EAWMI initialized in GCFS2 for December has a prediction skill of 0.42 after removing the ENSO signal, indicating that the sea-ice coverage in the Barents–Karabakh region in winter (BK_SIC) is another source for prediction works. The weakened BK_SIC enhances the observed SH and EAWM. Moreover, the changes of BK_SIC in the model can increase the predictability of the northeastern SH, thereby improving the EAWM prediction initialized for December.