This paper provides an overview of nonlinear system identification methodologies. The theory and application of nonlinear system identification is vast, and this overview is not intended to be comprehensive. Rather, the attempt here is to illustrate some of the salient features and key aspects of nonlinear system identification, especially those most relevant to the practitioner. In particular, this overview focuses on important issues in nonlinear system idenfication that differ from those encountered in linear system identification, including tests for nonlinearity, model selection, and input signal considerations.