This paper explores a wide range of issues associated with research on mental models. Based on a functional perspective, mental models are defined as the mechanisms whereby humans generate descriptions of system purpose and form, explanations of system functioning and observed system states, and predictions of future system states. Specifically, this paper reviews the ways in which different domains define mental models, characterize the purposes of such models, and attempt to identify the forms, structures, and parameters of models. The resulting distinctions among domains are described in terms of two dimensions: nature of model manipulation and level of behavioral discretion. Emerging salient issues include: (1) accessibility of mental models; (2) forms and content of representation; (3) nature of expertise; (4) cue utilization; and (5) instructional issues. Prospects for dealing with these substantive issues are presented. Limits in identifying mental models are due to the likelihood that the models are dynamic entities that can have a multiplicity of forms, biases imposed by scientists' own mental models, etc. Innovative (and validated) empirical approaches involving traditional experimental methods with newer methods (such as computational modeling and linguistic analysis) are recommended. A 94-item list of references is included. (PN)