Lethal controls have been used to control human-wild boar conflicts. However, these methods do not work satisfactorily, as their effectiveness is variable. Previous study has revealed that a reason for this variation is inter-individual differences in damage-causing behavior (i.e., damagecausing vs. non-damage-causing wild boars). To reduce crop damage effectively, selective culling should be conducted, but information on the density distribution of damage-causing wild boars is lacking. To build a practical density-distribution map of damage-causing wild boars, we examined the relationship between crop-damage data and 2 1 quasi-density maps (B-cpue, B-dm, and PC maps constructed using CPUE (catch-per-unit-effort) data, wild boar-distribution binary data, and principal components of B-cpue and B-dm, respectively). Regression analyses indicated that binary wild boar-distribution data (B-dm) had the best potential for development into a relative-density map. Binary data can be easily collected with little time, cost, or effort; thus, wildlife managers can use this method for effective management. Damage-causing factors include not only wild boar density, but also environmental factors (e.g., topography). Therefore, wildlife managers should recognize which factors induce damage in each region. If high density is the main damage-inducing factor, wildlife managers can use a lethal control method, but if damage-inducing factors are environmental, nonlethal methods such as fencing might be employed. Our density map enables wildlife managers to select areas in which intensive culls of damage-causing wild boars should be conducted.