A study was done to identify factors contributing to injury severity at freeway diverge areas and to evaluate impacts of the factors. Crash data and roadway information were collected at 231 freeway exit segments in Florida. Injury severity prediction models were developed by using partial proportional odds regression, which relaxes the restriction that all regression coefficients be the same across output values and allows one or more regression coefficients to differ across outcome levels. The analysis results indicated that the partial proportional odds model is more flexible and provides much better results than does the ordered probit model for fitting injury severity data. Factors that significantly influence injury severity at freeway diverge areas include length of deceleration and ramp lanes, curve and grade at diverge areas, light and weather conditions, alcohol or drug involvement, heavy-vehicle involvement, number of lanes on main lines, average daily traffic on main lines, surface condition, land type, and crash type. It can also be concluded that exit ramp types (single-lane exit ramps, single-lane exit ramps with a taper, two-lane exit ramps with an optional lane, and two-lane exit ramps without an optional lane) have no significant effects on injury severity at freeway diverge areas.