Blood is a regulated exceptional genetic biological resource. In response to the issue of easy oxidation and deterioration in traditional blood spectral detection, dynamic confocal Raman fluorescence spectroscopy technology based on biomimetic blood vessels was used to conduct blood species identification research on six types of poultry and livestock, including pigs, horses, pigeons, chickens, ducks, and geese. The preprocessing process of the original spectrum includes baseline removal, smoothing, and normalization. Linear discriminant analysis is used to reduce the dimensionality of spectral data, and then support vector machines are used to establish recognition models. Gaussian kernel functions are selected, and the parameters C and γ Make their classification accuracy the highest, the optimal C and γ 0.2 and 0.134, respectively. The recognition accuracy of the artificial fish school support vector machine model reaches 97.2%. The dynamic confocal Raman fluorescence spectrum based on biomimetic blood vessels used in this article can meet the requirements of blood safety and efficiency detection, and the algorithm model optimized by the artificial fish school algorithm for support vector machine parameters shows good classification performance.