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This chapter is excerpted from ‘The Art of Computer Modeling for Business Analytics: Paradigms and Case Studies'. In just about every sphere of business today, companies routinely utilize computer models to help make decisions. These models take many forms, from simple spreadsheets to sophisticated computer simulations. They may be bespoke models built for a specific company or they may be commercial software packages designed to be used by many different companies. They can be intended for one-time use to help decision makers think through a significant business decision or they can be tools designed for ongoing use within a company. They may be static or dynamic, deterministic or stochastic. The specific reasons for building a model are as varied as the models themselves, but the chief underlying reason is to assess the impact of a decision or a set of decisions on business performance. Based on that assessment, model users will make recommendations and take actions. The tacit assumption is that the model captures the relevant factors at a sufficient level of detail to make accurate projections and that, therefore, the conclusions drawn from the model are reasonable. The validity of the model thus depends on a host of judgments that the model builder makes in constructing the model-some transparent, others implicit. These judgments are what make building a computer model more of an art than a science. This book is about constructing and using computer models to help decision makers in the business world make more informed decisions. It is intended to provide useful paradigms and case studies for individuals who are interested in building effective decision models-ones that will get used to drive important business decisions. The focus is on practice, not theory. In particular, the book does not focus on the underlying methods for building models-for example, how to construct a discrete event simulation, how to solve a linear program, or how to perform a multivariable linear regression. My goal rather is to demonstrate, mainly through case studies, how to build effective models quickly and inexpensively, using software that is widely available and often free. It is meant as a practical guide, informed by my experience building such models for an array of businesses in diverse industries.