This study specifically investigated a range of vehicle-related factors that are associated with a lower risk of serious or fatal injury to a belted driver in a head-on collision. This analysis investigated a range of structural characteristics, quantities that describes the physical features of a passenger vehicle, e.g., stiffness or frontal geometry. The study used a datamining approach (classification tree algorithm) to find the most significant relationships between injury outcome and the structural variables. The algorithm was applied to 120,000 real-world, head-on collisions, from the National Highway Traffic Safety Administration's (NHTSA's) State Crash data files, that were linked to structural attributes derived from frontal crash tests performed as part of the USA New Car Assessment Program. As with previous literature, the analysis found that the heavier vehicles were correlated with lower injury risk to their drivers. This analysis also found a new and significant correlation between the vehicle’s stiffness and injury risk. When an airbag deployed, the vehicle’s stiffness has the most statistically significant correlation with injury risk. These results suggest that in severe collisions, lower intrusion in the occupant cabin associated with higher stiffness is at least as important to occupant protection as vehicle weight for self-protection of the occupant. Consequently, the safety community might better improve self-protection by a renewed focus on increasing vehicle stiffness in order to improve crashworthiness in head-on collisions.