Commonly used crude measures of disease risk or relative risk in a family, such as the presence/absence of disease or the number of affected relatives, do not take into account family structures and ages at disease occurrence. The Family History Score incorporates these factors and has been used widely in epidemiology. However, the Family History Score is not an estimate of familial relative risk; rather, it corresponds to a measure of statistical significance against a null hypothesis that the family's disease risk is equal to that expected from reference rates. In this paper, the authors consider an estimate of familial relative risk using the empirical Bayes framework. The approach uses a two-level hierarchical model in which the first level models familial relative risk and the second considers a Poisson count of the number of affected relatives given the familial relative risk from the first level. The authors illustrate the utility of this methodology in a large, population-based case-control study of breast cancer, showing that, compared with commonly used summaries of family history including the Family History Score, the new estimates are more strongly associated with case-control status and more clearly detect effect modification of an environmental risk factor by familial relative risk.