The ability to detect recent hybridization between dogs and wolves is important for conservation and legal actions, which often require accurate and rapid resolution of ancestry. The availability of a genetic test for dog-wolf hybrids would greatly support federal and legal enforcement efforts, particularly when the individual in question lacks prior ancestry information. We have developed a panel of 100 unlinked ancestry-informative SNP markers that can detect mixed ancestry within up to four generations of dog-wolf hybridization based on simulations of seven genealogical classes constructed following the rules of Mendelian inheritance. We establish 95 % confidence regions around the spatial clustering of each genealogical class using a tertiary plot of allele dosage and heterozygosity. The first- and second-backcrossed-generation hybrids were the most distinct from parental populations, with >90 % correctly assigned to genealogical class. In this article we provide a tool kit with population-level statistical quantification that can detect recent dog-wolf hybridization using a panel of dog-wolf ancestry-informative SNPs with divergent allele frequency distributions.