To identify factors influencing severity of injury to older drivers in fixed object-passenger car crashes, two sets of sequential binary logistic regression models were developed. The dependent variable in one set of models was driver injury severity, whereas for the other it was the crash severity (most severe injury in the crash). For each set of models, crash or injury severity was varied from the least severity level (no injury) to the highest severity level (fatality) and vice versa. The source of data was police crash reports from the state of Florida. The model with the best fitting and highest predictive capability was used to identify the influence of roadway, environmental, vehicle, and driver related factors on severity. Travel speed, restraint device usage, point of impact, use of alcohol and drugs, personal condition, gender, whether the driver is at fault, urban/rural nature and grade/curve existence at the crash location were identified as the important factors for making an injury severity difference to older drivers involved in single vehicle crashes.