We developed and validated a density-adjusted spatial model to predict moose (Alces alces) highway-crossing probability to see if the model could be used as an index of moose–vehicle collision risk. We installed Global Positioning System telemetry collars on 47 moose in the north of the Laurentides Wildlife Reserve, Québec, for 2–36 months. We recorded only 84 highway crossings in spring (0.29% of 28,967 2-hr steps) and 122 crossings in summer (0.18% of 68,337 2-hr steps), despite a high sampling effort and having captured moose close to highways. Moose movement rates during movement steps crossing a highway were on average 3 times higher than during the steps preceding or following highway crossing. Paths used by moose when crossing a highway were characterized by a high proportion of food stands, low proportion of lakes and rivers, and topography typical of a valley. Highway-crossing sites were located in valleys with brackish pools and forest stands providing coniferous cover but a low proportion of lakes and rivers. We adjusted moose crossing probability for local variation in moose density using aerial survey data and assessed crossing probability along the highways in the entire Laurentides Wildlife Reserve. We tested the model using moose–vehicle accident data from 1990 to 2002. The relationship between the density-adjusted crossing probability and number of accidents was relatively loose at the 1-km scale but improved markedly when using longer highway sections (5–15 km; r > 0.80). Our results demonstrate that roads and their surroundings are perceived as low-quality habitat by moose. We also conclude that road segments installed along secondary valleys could be a highly strategic site to deploy mitigation measures such as fences and that it could be desirable to increase the width of road shoulders to reduce forest cover and to eliminate brackish pools to reduce cervid–vehicle collisions. We suggest using empirical data such as location of vehicle–wildlife collisions to plan mitigation measures at a fine scale.