Monitoring of the grey wolf (Canis lupus L. 1758) is an important tool especially when harvest of individuals is used for its management. Within this thesis, we used systematic and opportunistic monitoring methods, aiming the collection of evidence of presence of a specific pack. Main aim of the study was to estimate the fluctuation of their abundance and to assess areas of intensive use (hotspot). Study area (25 km2) was located on the hill Trstie, in part of the Stolica Mountains and close to the border of the buffer zone of Muran Plateau National Park. Fieldwork took place from November 2018 until March 2020, in a total of 48 days in three consecutive days per month. Within the first day we systematically performed a transect. On the second and third day we performed random transects in an opportunistic way, based on the results from the first day. Length of systematic transect was 8 km and opportunistic transect varied between 3.5km and ~15.3km. In total, We covered a distance of 486 km and recorded 608 evidences of presence of wolves. Evidence of presence of wolf records comprehended wolf tracks, faeces, urine, resting sites, rendezvous areas and others. The data was then analysed based on the concentration of the records. We assessed the space-time activity of the wolf pack within the study area based on the evidence of presence collected, considering two seasons: the spring-summer and autumn-winter seasons. To determine the hotspot areas we processed our records in ArcGIS using Kernel Density Estimation tool (KDE50). Results suggested two to three possible hotspots in the study area. Using the KDE results and in order to increase the estimation accuracy we installed four camera traps. Camera trap records showed to be successful and estimations of wolves were confirmed. The monitored wolf pack size varied from 6–13 individuals and we confirmed two reproductions in the 2 consecutive years. Our results suggest that systematic and opportunistic assessment of wolf population using non-invasive methods can provide much accurate and valuable data to support stakeholders’ decisions within the management of wolves.