Robust population estimation of rare or elusive threatened species lacking distinct identifiable features poses a challenge in the field of conservation and management. The Asiatic black bear (Ursus thibetanus) is one such species. Methodological frameworks—such as radiotelemetry, genetic sampling, and camera-trapping—though crucial and advantageous, sometimes require additional information through invasive methods for individual identification. In this study, we estimated the population density of Asiatic black bear in 2 protected areas in the Indian Himalayan Region without information on individual identification. We conducted the study through a spatial capture–recapture framework using camera traps in the summer during May–July 2018 in Daranghati Wildlife Sanctuary (WLS) and May–July 2019 in Rupi Bhaba WLS. Using the recently developed Spatial Presence–Absence model, we estimated g₀ (detection probability), σ (scale or movement parameter related to home range of the species), and N (population size) of Asiatic black bears from the camera-trap data using a Bayesian framework. We estimated a population density of 2.5 individuals/100 km² (95% Credible Interval = 1.42–9.63 individuals/100 km²) from Daranghati WLS and 0.3 individuals/100 km² (95% Credible Interval = 0.2–0.7 individuals/100 km²) from Rupi Bhaba WLS. Abundance estimates produced by extrapolating these densities were 11 Asiatic black bear individuals (95% Credible Interval = 4–27) from Daranghati WLS and 2 Asiatic black bear individuals (95% Credible Interval = 1–3) from Rupi Bhaba WLS. This is the first population estimate of Asiatic black bear from the Indian Himalaya without individual identification. We recommend that this method, which provides minimal sampling bias and ease of sampling, can be replicated in other mountainous landscapes for a robust density estimation of this species.