Daily output from the hindcasts by the National Centers for Environmental Prediction (NCEP) Climate Forecast System version 2 (CFSv2) is analyzed to understand the skill of forecasting atmospheric variability on quasi-biweekly (QBW) time scale. Eight dominant quasi-biweekly oscillation (QBWO) modes identified by the extended empirical orthogonal function analysis are focused. In the CFSv2, QBW variability exhibits a significant weakening tendency with lead time for all seasons. For most QBWO modes, the variance drops to only 50 % of the initial value at lead time of 11–15 days. QBW variability has better prediction skill in the winter hemisphere than in the summer hemisphere. Skillful forecast can reach about 10–15 days for most modes but those in the winter hemisphere have better forecast skills. Among the eight QBWO modes, the North Pacific mode and the South Pacific (SP) mode have the highest forecast skills while the Asia–Pacific mode and the Central American mode have the lowest skills. For the Asia–Pacific and Central American modes, the forecasted QBWO phase shows an obvious eastward shift with increase in lead time compared to observations, indicating a smaller propagating speed. However, the predicted feature for the SP mode is more realistic. Air–sea coupling on the QBW time scale is perhaps responsible for the different prediction skills for different QBWO modes. In addition, most QBWO modes have better forecasting skills in El Nino years than in La Nina years. Different dynamical mechanisms for various QBWO modes may be partially responsible for the differences in prediction skill among different QBWO modes.