To evaluate vehicle occupant injury risk, finite element human body models (HBMs) can be used in vehicle crash simulations. HBMs can predict tissue loading levels, and the risk for fracture can be estimated based on a tissue-based risk curve. A probabilistic framework utilizing an age-adjusted rib strain-based risk function was proposed in 2012. However, the risk function was based on tests from only twelve human subjects. Further, the age adjustment was based on previous literature postulating a 5.1% decrease in failure strain for femur bone material per decade of aging. The primary aim of this study was to develop a new strain-based rib fracture risk function using material test data spanning a wide range of ages. A second aim was to update the probabilistic framework with the new risk function and compare the probabilistic risk predictions from HBM simulations to both previous HBM probabilistic risk predictions and to approximate real-world rib fracture outcomes. Tensile test data of human rib cortical bone from 58 individuals spanning 17–99 years of ages was used. Survival analysis with accelerated failure time was used to model the failure strain and age-dependent decrease for the tissue-based risk function. Stochastic HBM simulations with varied impact conditions and restraint system settings were performed and probabilistic rib fracture risks were calculated. In the resulting fracture risk function, sex was not a significant covariate—but a stronger age-dependent decrease than previously assumed for human rib cortical bone was evident, corresponding to a 12% decrease in failure strain per decade of aging. The main effect of this difference is a lowered risk prediction for younger individuals than that predicted in previous risk functions. For the stochastic analysis, the previous risk curve overestimated the approximate real-world rib fracture risk for 30-year-old occupants; the new risk function reduces the overestimation. Moreover, the new function can be used as a direct replacement of the previous one within the 2012 probabilistic framework.