Over the last 15 years, there has been an explosive growth in the use of statistical modeling for predicting which consumers are most likely to respond and/or purchase products advertised by companies. These modeling techniques have progressed from a simple version of “judgmental modeling”, or assigning a random number of points for things that experienced marketers “knew” to be true, to today’s heavily-statistical output, generally built by well-trained statisticians who nevertheless may have little-to-no knowledge of the marketing space. Because the worlds of consumer marketing and statistical analysis don’t necessarily cross very often, it’s more important than ever for marketers to understand and review the work being performed by their modeling staff. This paper is designed as an overview for the marketing professional of the best practices in building statistically-accurate marketing models.