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The growing accuracy and sophistication of models in many fields often lead, paradoxically, to limitations upon their use. Computational cost, excessive input data requirements, and difficulty in interpretation of the implications of the model are typical impediments to the broad use of many complex models. Repro-modeling is an approach which, in many cases, overcomes these problems by creating an efficient input/output approximation to the model. Practical methodological approaches to this straightforward concept are proposed, including a practical algorithm for obtaining a continuous multivariate piecewise linear approximation with subregions of general form given a small randomly distributed set of input/output samples. Three examples of the successful application of repro-modeling are outlined: the impact on air quality of a traffic-restriction policy, the design of effective traffic-responsive freeway on-ramp control algorithms, and the radar return from a complex object.