Reproductive synchrony is a widespread phenomenon found in many taxa, including plants and corals. However, compared with synchrony caused by environmental cues, knowledge of socially induced reproductive synchrony is limited, partly due to the difficulty of experimentally manipulating and/or making detailed behavioral observations of populations in the wild. In this study, we developed a novel modeling framework combining an individual-based model, a hierarchical Bayesian model, and an approximate Bayesian computation (ABC) to elucidate socially induced reproductive synchrony. This method was applied to time-series redd (i.e., spawning nests) count data in 30 wild populations of stream-dwelling Dolly Varden charr. The model with reproductive synchrony explained all the redd count data, whereas the null model, which did not include the synchrony, failed to reproduce the observed data in several populations. In addition, our models suggest that Dolly Varden should be able to adjust spawning by up to a week following other females to produce synchrony. No significant correlation was observed between reproductive timing and environmental factors, suggesting that the major cue for the synchrony was social rather than environmental. The presence of reproductive synchrony within but not among local populations suggests that predator satiation is not the main driver of the synchrony; rather, other mechanisms must exist in the Dolly Varden, such as induced monogamy or polygamy, or avoidance of nest superimposition. This study has demonstrated the effectiveness of using individual-based and hierarchical modeling together with an ABC parameter estimation method in behavioral ecological studies.