The efficiency of the management of predations on livestock by gray wolves (Canis lupus) through culling is under debate. Evaluating wolf culling efficiency requires to simultaneously analyze the effects of culling on the wolf population and the repercussions of these population changes on livestock predation. This protocol is technically difficult to implement in the field. To properly assess culling efficiency, we provided an integrated and flexible individual-based model that simulated interactions between wolf population dynamics, predation behavior and culling management. We considered many social processes in wolves. We calibrated the model to match the Western Alps as a case study. By considering the prey community in this area and the opportunistic nature of wolf predation, we assumed that predation on livestock at the wolf territory level increased with pack’s food needs. Under this assumption and considering livestock availability as high and livestock vulnerability as uniform in space and time, culling maintained wolf population size and predation risks at low levels. Contrary to what was expected, culling decreased the mean annual proportions of dispersing wolves in our simulations, by speeding settlement. This population-level mechanism compensated for the high mortality and the pack instability caused by culling. Compensation was however dependent on the selectivity and the timing of culling. When executed before the natural mortality module in our model, the selective culling could undermine replacement of lost breeders and therefore decrease wolf population resilience to culling. Our model gives insights about culling effects in one specific simulated context, but we do not expect that our assumption about predation behavior necessarily holds in other ecological contexts and we therefore encourage further explorations of the model.