Polymerase chain reaction (PCR) detection is a commonly used method for species identification of meat products. However, this method is not suitable for the analysis of meat products containing multiple mixtures. This study aimed to test whether next-generation sequencing (NGS) technology could be used as a method for the certification of mixed meat products. In this study, five kinds of common meat (pigs, cattle, sheep, chickens, and ducks) were mixed as samples with different proportions. The primers designed from mitochondrial 16S rRNA and nuclear genome gene (growth hormone receptor, GHR), respectively, were used to detect these meats. The sequencing results of NGS were analyzed using a self-designed bioinformatics program. The fragments with similar sequences were classified and compared with the database to determine their species. The results showed that all five kinds of meat components could be correctly identified using these two primers. The meat composition could be detected as low as 0.5 in the mixed samples using the NGS technology targeting GHR gene fragments, which was superior to those targeting mitochondrial 16S rRNA. However, the quantitative detection of species in the mixture was not likely to be quite accurate due to the amplification bias of PCR amplification. These results showed that the NGS technology could be applied to identify meat species in mixtures.