In 1976 the U.S. Congress removed the threat of withdrawal of certain highway funds from states that failed to enact motorcycle helmet laws. Since then over half the states have either repealed or weakened these laws. Most researchers in the field agree that this has lead to a significant increase in injuries and fatalities among motorcyclists involved in accidents. Potential limitations of many of the studies on which these conclusions are based include the facts that fatalities can result from injuries to parts of the body not protected by helmets and that other factors, such as speed and alcohol use, are not taken into account, usually due to lack of data. The former will result in a loss of power and the latter in the introduction of bias. In this article I model the level of head injury rather than the fatality rate and build a multivariate model that includes the other factors. The basic model is an ordered probit model with heteroscedasticity in the errors. The adequacy of the model is tested by Lagrange multiplier and goodness-of-fit tests. The former include tests for the normality of the errors and the specification of the regressors. Predictions from the model include that helmets lead to a 42% increase in the number of riders with no head injury and a $1,700 per rider decrease in the direct medical cost of treating the riders.