Aiming at the physical evidence of heroin mixtures and methamphetamine mixtures, a spectral identification method for drug mixtures based on the support vector machine-multilayer perceptron(SVM-MLP) fusion model is proposed. In the experiment, 90 sets of spectral data of the mixture of heroin, methamphetamine and other substances were obtained, and the baseline automatic correction and peak area normalization were used to eliminate noise and use principal component analysis extract characteristic wavenumber data spectral data fusion classification model based on SVM and MLP. The result shows that the SVM model based on Gaussian kernel function, linear kernel function, and polynomial kernel function can achieve accurate classification of 97.8%, 97.8%, and 95.6% of heroin mixture samples, respectively. The MLP model can achieve 96.5% for methamphetamine mixture samples accurate classification. The SVM-MLP fusion model is non-destructive, convenient and efficient is helpful for the identification of drug evidence in anti-drug cases and the judicial sentencing of the person involved has a certain universality and reference significance.