The Mathematical Modeling Performance Task Guide introduces the steps to developing a mathematical model that presents real world, empirical data to support understanding and analysis, and to justifying the use of this model as appropriate within the problem context.

Creating and using models is fundamental to the study of mathematics. While mathematical models are often simple, the process of developing even basic models requires a great deal of thought and understanding, calling on both algorithms and hueristics. Mathematical modeling is a powerful performance task because it has applications not only in math, but across all the STEM subjects.

Student choice can be encouraged in a number of ways. Students can choose real-world phenomena to model, find or generate data, and choose to argue a specific position their model elucidates. If students are given the problem context and/or data, they can determine which model is appropriate to represent this data and discuss the affordances and limitations of their model. In some instances, they can also choose the resources they review, the data they will present, and/or the audience for their model.

Creating and using models is fundamental to the study of mathematics. Models are used in almost all professions, including medicine, business, legal services, educational tools and services, engineering, news, and politics.  They are used within these fields in various ways, including sales presentations, advertising, visual arguments, website design, presentations, and reporting.

There are many possible audiences for mathematical models: simple graphs and charts can be created to help others understand complex data; Excel and CADD can be used to create virtual models of prototypes too costly to create; complex systems can be translated to mathematics to make predictions about likely outcomes of decisions.