1. A predictive model method, comprising: using a computer to perform at least one of the steps of: receiving first input data into a plurality of different types of initial predictive models to develop an initial model configuration by selecting an input data set from the plurality of predictive models using a variable selection algorithm after a training of each predictive model type is completed; receiving the input data set from said initial model configuration as an inputs into a second, model stage to develop an improvement to said initial model configuration and input data set as an output; and receiving said second model stage output as an input into a third predictive model stage to develop and output a final predictive model where all the input data represents a physical object or substance and where the final predictive model consists of a linear predictive model or a nonlinear predictive model.