Based on discussion on the theories of support vector machines (SVM),an one-step prediction model for time series prediction is presented,wherein the chaos theory is incorporated.Chaotic character of the time series is taken into account in the prediction procedure; parameters of reconstruction-delay and embedding-dimension for phase-space reconstruction are calculated in light of mutual-information and false-nearest-neighbor method,respectively.Precision and functionality have been demonstrated by the experimental results on the basis of the prediction of Lorenz chaotic time series. Based on discussion on the theories of support vector machines (SVM), an one-step prediction model for time series prediction is presented, where the chaos theory is incorporated. Chaotic character of the time series is taken into account in the prediction procedure; parameters of reconstruction-delay and embedding-dimension for phase-space reconstruction are calculated in light of mutual-information and false-nearest-neighbor method, respectively. Precision and functionality have been demonstrated by the experimental results on the basis of the prediction of Lorenz chaotic time series.