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A prediction model for hand prehensile movements was developed and validated. The model is based on a new approach that blends forward dynamics and a simple parametric control scheme. In the development phase, model parameters were first estimated using a set of hand grasping movement data, and then statistically analyzed. In the validation phase, the model was applied to novel conditions created by varying the subject group and size of the object grasped. The model performance was evaluated by the prediction errors under various novel conditions as compared to the benchmark values with no extrapolation. Analyses of the model parameters led to insights into human movement production and control. The resulting model also offers computational simplicity and efficiency, a much desired attribute for digital applications.