This chapter discusses models based on the reciprocals of variables. It reconsiders these models in their formulation as inverse polynomials, examining the properties of the models briefly and then using them to analyze data in an example that illustrates many of the techniques of analysis for nonlinear models. To see why nonlinear models should be useful, it is necessary to consider why linear models are inadequate to model biological situations. The chapter also discusses three particular types of nonlinear models. The first uses exponential terms to represent a tendency to an asymptote. A second type of nonlinear model that is commonly used is based on reciprocal relationships, typically the rectangular hyperbola. A third type of nonlinear model is the logistic curve, extensively used to represent the growth of organisms from a very small initial stage during which growth is proportional to size, to later stages when size approaches an asymptote.