This question is currently spiritedly discussed in the Liked-in group Advanced Business Analytics (just as en example). Predictive modeling is the process of modeling future behavior. The model might be the discovery from a theory, knowledge or extracted from data samples. A predictive model forecasts.
I expect from predictive models that they are interpretable and computational (white box - black box principles drive the spiral of innovation in computation (and math)).
In general, there seem to be uncertainty about the process of generating/manipulating models and their usage. If you want to automate the whole process you need to understand that model generators/manipulators act on (program)trees and the model acts on tuples. Genetic algorithms act on tuples, evolutionary programming acts on program trees.
If you want to do both in one environment you need symbolic and numerical computation, pattern matching, .... Mathematica. (you can implement a genetic algorithm practically in any language, but a general Fit function that is result of an evolutionary selection and combination process (by crossing over subtrees of nested functions and operators) ... ?!)
