This paper describes a statistical forecasting system for the short-term prediction (up to 48 h ahead) of the wind energy production of a wind farm. The main feature of the proposed prediction system is its adaptability. The need for an adaptive prediction system is twofold. First, it has to deal with highly nonlinear relationships between the variables involved. Second, the prediction system would generate predictions for alternative wind farms, as it is made by the system operator for efficient network integration. This flexibility is attained through (i) the use of alternative models based on different assumptions about the variables involved; (ii) the adaptive estimation of their parameters using different recursive techniques; and (iii) using an on-line adaptive forecast combination scheme to obtain the final prediction. The described procedure is currently implemented in SIPREÓLICO, a wind energy prediction tool that is part of the on-line management of the Spanish Peninsular system operation. © 2005 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.