Movement ecology is flourishing thanks to advancements of tracking technology and, in parallel, a proliferation of methods to infer behavior from individual trajectories. An emerging direction is the use of telemetry data to estimate reproductive success, which connects movement to components of individual fitness. Here, we introduce a method to locate breeding attempts and estimate their outcome from avian GPS-tracking data, implemented in the R package 'nestR'. We identified nest sites based on the analysis of recursive movements of breeding individuals acting as central place foragers.Using trajectories with known breeding attempts, we estimated a set of species-specific criteria for the identification of nest sites, which we further validated using non-reproductive individuals as controls.We then estimated individual nest survival as a measure of reproductive outcome from nest-site revisitation histories during breeding attempts, using a Bayesian hierarchical modeling approach that accounted for temporally variable re-visitation patterns, probability of visit detection, and missing data.We illustrated the application of our method and evaluated its performance using data for three species: wood storks (Mycteria americana), lesser kestrels (Falco naumanni), and Mediterranean gulls (Ichthyaetus melanocephalus). Across the three species, positive predictive value of the nest-site detection algorithm was between 73-100% and sensitivity was between 87-92%, and we correctly estimated the outcome of 86-100% breeding attempts. Our method can be broadly applied to estimate individual reproductive outcome in a variety of central place foragers, bridging the gap between movement behavior, environmental factors, and their fitness consequences.