Efforts to manage small and medium-sized pelagic fishes (SMPF) using traditional stock assessment methods are hampered by the elusive relationship between spawning stock biomass and recruitment. We propose to compute a reproductive resilience index (RRI) in three steps: ( i) we selected 16 biological traits related to distinct aspects of SMPF reproductive biology and characterized by a continuous (e.g., growth rate) or ordinal variable (e.g., spawning site fidelity) scored from 1 to 5 (1 representing a low contribution of the trait to reproductive resilience); ( ii) an expert panel assigned the traits’ scores to five exploited species in the southern Humboldt Current Large Marine Ecosystem; ( iii) a Bayesian Belief Network (BBN) model was used to estimate an RRI based on the combination of the traits’ scores. The BBN was used to explore environmental effects on the species’ RRI, as some reproductive traits can show intraspecies variability under external forces (e.g., fishing pressure). Through proving the RRI application to detect variability in species’ resilience at local time series, we show how the resulting RRI can be interpreted by fishery managers to improve the current management of SMPF.