Seat comfort is driven in part by the fit between the sitter and seat. Traditional anthropometric data provide little information about the size and shape of the torso that can be used for backrest design. This study introduces a methodology for using three-dimensional computer models of the human torso based on a statistical analysis of body shapes for conducting automated fit assessments. Surface scan data from 296 men and 417 women in a seated posture were analyzed to create a body shape model that can be adjusted to a range of statures, body shape, and postures spanning those typical of vehicle occupants. Finite-element models of two auto seat surface were created, along with custom software that generates body models and postures them in the seat. A simple simulation technique was developed to rapidly assess the fit of the torso relative to the seat back. The methodology developed in this study will enable automated virtual fitting trails considering a wide range of body sizes and shapes, allowing statistical evaluations of seat fit within a specific sitter population. Further refinement of the method will allow prediction of seat pressure distribution, which may be usefully related to subjective assessment of seat fit.