A systems modeling approach is presented for assessment of harm in the automotive crash environment. The recent surge in light truck sales has highlighted the need to evaluate these vehicles’ aggressivity in two-vehicle crashes while also considering potential self protection benefits in single-vehicle crashes. The methodology consists of parametric simulation of several controlled accident variables, with case results weighted by the relative frequency of each specific event. A hierarchy of models is proposed, consisting of a statistical model to define the crash environment and assign weighting factors for each crash situation case, and vehicle models for parametric simulation of crash events. Approximating functions are utilized to estimate occupant harm metrics based on vehicle crash response. Head and chest injury results for each case are converted to harm vectors, in terms of probabilistic Abbreviated Injury Scale (AIS) distributions. These harm vectors are weighted by each case’s probability as defined by the statistical model, and summed to obtain a total estimate of harm for the crash environment. The methodology is applied to a subset impact environment consisting of single- and two-vehicle frontal collisions among passenger cars and light trucks. The model is validated against injury field data, and is found to accurately reflect trends in distribution of injury severity. The model is also exercised for variable sensitivity analyses, wherein changes in light truck/car population mix and LTV frontal stiffness are evaluated in terms of their effects on occupant harm within the frontal crash environment.