Finding the best possible subset of variables to put in a model has been a frustrating exercise. Many methods of variable selection exist, but none of them is perfect. Moreover, they do not create new variables, which would enhance the predictive power of the original variables themselves. Furthermore, none use a criterion that addresses the specific needs of database marketing models. I present the GenIQ Model as a methodology that uses genetic modeling to find the best variables for database marketing models. Most significantly, genetic modeling can be used to address the specific requirements of database marketing models.