Understanding disease transmission dynamics, which are in part mediated by rates and patterns of social contact, is fundamental to predicting the likelihood, rate of spread, impacts, and mitigation of disease outbreaks in wildlife populations. Contact rates, which are important parameters required for epidemiologic models, are difficult to estimate. The endangered Hawaiian monk seal (Neomonachus schauinslandi) may be particularly vulnerable to morbillivirus outbreaks, due to its low abundance, lack of genetic diversity, and history of isolation from mammalian diseases. Morbillivirus epizootics have had devastating effects on other seal populations. We constructed social networks based on visual observations of individually identifiable monk seals associating onshore to estimate contact rates, assuming random mixing, and also to investigate contact patterns of different age and sex classes. Contact rates estimated from two island populations in 4 yr were remarkably similar, indicating any two individuals have about a one in 1,000 chance of making contact on any given day. Further, contact patterns within and among age and sex classes were statistically different from random. The methods we used could be broadly applied to empirically derive contact rates using association data. These rates are critical for epidemiologic modelling to simulate wildlife disease outbreaks and to inform science-based prevention and mitigation programs.