With a continuous expansion of the number and activity of wild animals induced by ecological conservation and restoration efforts, the human-wildlife conflict is becoming more prominent across China. There have been frequent and severe incidents of crop damage caused by wildlife. In this paper, we investigate the crop losses caused by wildlife in the rural districts of Beijing, using a unique dataset of 31,573 observations from 2009 to 2017. Through statistical tests on the individual coefficients and the overall fitness, we find that a negative binomial generalized regression model describes the pattern of crop loss events more accurately, compared to an alternative Poisson model. The frequency of crop loss events is positively related to a village's distance from the river system but negatively associated with the distance from woodland, population density, and protective measures taken. The predicted frequencies of crop damage events are then used to correlate with the amounts of losses at the village level. Based on these results, we propose solutions for effective reduction of future crop losses and practical assessment of the likely damage compensation or insurance premium.