Risk assessments are performed to estimate the conditions under which individuals or populations may be harmed by exposure to environmental or occupational chemicals. In the absence of quantitative data in the human, this process is often dependent upon the use of animal and in vitro data to estimate human response. To reduce the uncertainty inherent in such extrapolations, there has been considerable interest in the development of physiologically based pharmacokinetic (PBPK) models of toxic chemicals for application in quantitative risk assessments. PBPK models are effective tools for integrating diverse dose-response and mechanistic data in order to more accurately predict human risk. Yet, for these models to be useful and trustworthy in performing the necessary extrapolations (species, doses, exposure scenarios), they must be thoughtfully constructed in accordance with known biology and pharmacokinetics, documented in a form that is transparent to risk assessors, and shown to be robust using diverse and appropriate data. This paper describes the process of PBPK model development and highlights issues related to the specification of model structure and parameters, model evaluation, and consideration of uncertainty. Examples are provided to illustrate approaches for selecting a "preferred" model from multiple alternatives.