The aim of investigation was to evaluate a traceability system to detect industrial chicken meat among indigenous products, considering issues that could affect assignment accuracy. The dataset included 2 Italian indigenous meat breeds, namely Bionda Piemontese (2 ecotypes) and Bianca di Saluzzo, one broiler line, and 3 layer lines. Assignment tests were performed using a standard panel of 28 microsatellite loci. To evaluate effects of inbreeding and substructure on assignment accuracy, a simulated dataset was prepared. Broilers and layers belong to homogeneous populations and never enter the clusters of indigenous breeds. Ambiguity or misallocation are expected between the Bionda ecotypes and between the 2 indigenous breeds, but it is unlikely that niche products provided by Bionda and Bianca will compete with one another. Non-random mating reduces accuracy, but only populations having weak genetic differentiation are involved, namely those that are less interesting to discriminate. The dataset can be used as a reference population to distinguish commercial meat from indigenous meat with great accuracy. Misallocations increase as number of loci decreases, but only within or between the indigenous breeds. A subpanel of the most resolving 14 loci keeps sufficient informative content to provide accuracy and to correctly allocate additional test samples within the reference population. This analytical tool is economically sustainable as a method to detect fraud or mislabeling. Adoption of a monitoring system should increase the value of typical products because the additional burden of molecular analyses would improve commercial grade and perception of quality.