Building and deploying an effective predictive model is not all about analytics and the math but also about framing up problems that matter, determining the questions that need to be answered and why answering them matters. Getting this right leads to defining the proper “target”, the “base” or “comparative” population, and what types of explanatory or influencing factors might describe or influence why the target is different than the rest of the population. All too often we see people diving into really complex models with tons of factors without first nailing down what they are trying to do. When this happens, the models typically don’t produce useful results and end up sitting on the sidelines and are not used by the organization. This chapter guides a user through the process of building effective predictive models.