Summary1. Reliable estimates of population parameters are often necessary for conservation management but these are hard to obtain for elusive, rare and wide‐ranging species such as wolvesCanis lupus.This species has naturally recolonized parts of its former habitat in Western Europe; however, an accurate and cost‐effective method to assess population trend and survival has not been implemented yet.2. We used open‐model capture–recapture (CR) sampling with non‐invasive individual identifications derived from faecal genotyping to estimate survival and trend in abundance for wolves in the Western Alps between 1999 and 2006. Our sampling strategy reduced individual heterogeneity in recaptures, thus minimizing bias and increasing the precision of the estimates.3. Young wolves had lower apparent annual survival rates (0·24 ± 0·06) than adult wolves (0·82 ± 0·04); survival rates were lower in the summer than in the winter for both young and adults. The wolf population in the study area increased from 21 ± 9·6 wolves in 1999 to 47 ± 11·2 wolves in late winter 2005; the population growth rate (λ = 1·04 ± 0·27) was lower than that recorded for other recolonizing wolf populations.4. We found a positive trend in wolf abundance, regardless of the method used. However, the abundance estimate based on snow‐tracking was on average 36·2% (SD = 13·6%) lower than that from CR modelling, because young dispersing wolves are likely to have lower sign detection rates in snow‐track surveys, a problem adequately addressed by CR sampling.5. Synthesis and applications.We successfully implemented a new method to assess large carnivore population trend and survival at large spatial scales. These are the first such estimates for wolves in Italy and in the Alps and have important management implications. Our approach can be widely applied to broader spatial and temporal scales for other elusive and wide‐ranging species in Europe and elsewhere.