A new identification approach is introduced for predicting the Dst index using multiresolution B-spline wavelet models based on an observational data set consisting of VBs, the solar wind parameter, as the input and the Dst index as the output. The relationship between the input VBs and output Dst is initially described using a B-spline wavelet model. This model is then simplified using an orthogonal least squares and error reduction ratio (OLS-ERR) algorithm by selecting the significant model terms to produce a parsimonious wavelet model. Forecasts of the Dst index are then computed based on this model.