In surveys of hybrid zones, dominant genetic markers are often used to identify individuals of hybrid origin and assign these individuals to one of several potential hybrid classes. Quantitative analyses that address the statistical power of dominant markers in such inference are scarce. In this study, dominant genotype data were simulated to evaluate the effects of, first, the number of loci analyzed, second, the magnitude of differentiation between the markers scored in the groups that are hybridizing, and third, the level of genotyping error associated with the data when assigning individuals to various parental and hybrid categories. The overall performance of the assignment methods was relatively modest at the lowest level of divergence examined (Fst ~ 0.4), but improved substantially at higher levels of differentiation (Fst ~ 0.67 or 0.8). The effect of genotyping error was dependent on the level of divergence between parental taxa, with larger divergences tempering the effects of genotyping error. These results highlight the importance of considering the effects of each of the variables when assigning individuals to various parental and hybrid categories, and can help guide decisions regarding the number of loci employed in future hybridization studies to achieve the power and level of resolution desired.