Boreal ecosystems are experiencing extensive changes because of anthropogenic stressors such as climate change. Information on density of species at multiple sites is vital to understand and manage the impact of these changing conditions on boreal forest communities. Yet, for most boreal forest species, including the vast majority of mammals, obtaining reliable estimates of density is exceedingly difficult. Recently developed methods for the estimation of densities of unmarked animals from camera-trapping data could help to overcome this hurdle, but have not yet been empirically validated in many ecosystems. Here, we assess the ability of camera traps to estimate density of snowshoe hare (Lepus americanus) using three different models: the random encounter model (REM), the random encounter and staying time (REST) model, and the time-to-event (TTE) model. We additionally evaluate the relationship between hare density and two simple indices based on camera detection rate and pellet counts. Across 13 sites in North Central Washington, United States, we compared live-trapping spatially explicit capture–recapture (SECR) estimates of density to the three camera-based density models and the two indices. We found that the camera-based models, in particular the REM and REST models, performed well in estimating densities consistent with the live-trapping data, with an average difference in density from SECR-based estimates of only 0.12 and 0.13 hares/ha, respectively. Both indices also had strong predictive relationships with hare density. Our results show that, owing to their noninvasive nature and relative ease of application, camera-based methods could be used to obtain hare density estimates at much larger spatiotemporal scales than have been applied to date. Given the keystone role of hare in boreal ecosystems, and emerging evidence of hare range retraction, the ability to estimate densities across many sites is a key tool for hare conservation and management. Moreover, our results are highly encouraging for the application of camera-based methods to obtain density estimates on a wide variety of boreal forest species, though additional validation will be necessary.