Abstract: A nuclear magnetic resonance (NMR) system, and related method, develops two or more regression equations or models for a particular polymer property of interest (e.g., melt index or MI) during a calibration procedure using known samples of a material. The polymer material can be, for example, a plastic (e.g., polyethylene, polypropylene, or polystyrene) or a rubber (e.g., ethylene propylene rubber). Regression models for one or more discrete (i.e., two-valued) variables also are developed during calibration, and these models allow a prediction to be made about which of the two or more property (e.g., MI) models should be used for any particular sample of unknown material. The prediction obtained from the discrete variable model indicates which of the two or more models will produce the most accurate estimation of the property of interest for the unknown sample. The best model is thus selected, and then it is used to estimate the property of interest.