We tested a panel of 13 highly polymorphic canine short tandem repeat (STR) markers for dog breed assignment using 392 dog samples from the 23 most popular breeds in Austria, Germany, and Switzerland. This STR panel had originally been selected for canine identification. The dog breeds sampled in this study featured a population frequency ≥1% and accounted for nearly 57% of the entire pedigree dog population in these three countries. Breed selection was based on a survey comprising records for nearly 1.9 million purebred dogs belonging to more than 500 different breeds. To derive breed membership from STR genotypes, a range of algorithms were used. These methods included discriminant analysis of principal components (DAPC), STRUCTURE, GeneClass2, and the adegenet package for R. STRUCTURE analyses suggested 21 distinct genetic clusters. Differentiation between most breeds was clearly discernable. Fourteen of 23 breeds (61%) exhibited maximum mean cluster membership proportions of more than 0.70 with a highest value of 0.90 found for Cavalier King Charles Spaniels. Dogs of only 6 breeds (26%) failed to consistently show only one major cluster. The DAPC method yielded the best assignment results in all 23 declared breeds with 97.5% assignment success. The frequency-based assignment test also provided a high success rate of 87%. These results indicate the potential viability of dog breed prediction using a well-established and sensitive set of 13 canine STR markers intended for forensic routine use.