Beef is an important edible meat in China. In recent years, with the increasing demand for beef, the phenomenon of pork being impersonated or added to beef for sale has become increasingly serious, and there is an urgent need for simple and rapid detection methods to monitor adulteration behavior. This study analyzed the three-dimensional fluorescence spectra of beef and pork to determine the wavelength difference of synchronous fluorescence. A synchronous fluorescence spectrum with a fixed wavelength difference of 160 nm was used to qualitatively distinguish and quantitatively analyze the doping of beef with pork. The discriminant accuracy of the test set, verification set, and prediction set samples are taken as the evaluation index of the qualitative Discriminative model: Correlation coefficient (r), corrected Root-mean-square deviation (RMSEC) and predicted Root-mean-square deviation (RMSEP) were used as the evaluation indicators of the quantitative analysis model. The experimental results show a significant difference in the three-dimensional fluorescence spectra between beef and pork. Beef has fluorescence peaks at Ex/Em values of 270/320, 330/400, 350/500, 430/515 and 410/570 nm, while pork has three fluorescence peaks at Ex/Em values of 270/320, 330/400 and 430/515 nm. By setting the synchronous fluorescence wavelength difference to 160 nm, three fluorescence peaks of beef can be collected, with two of them located at the peak. The correction set accuracy of the SVM qualitative Discriminative model for beef, pork, and adulterated meat was 97.56%, and the prediction accuracy was 92.31%. The PLS prediction model for pork addition in beef without treatment, MSC treatment, and SNV treatment was compared. The PLS model without treatment was the best, with r_c, r_p, RMSEC, and REMSP reaching 0.978 6, 0.959 0, 0.059 7, and 0.092 7, respectively. Therefore, the qualitative discrimination and quantitative analysis detection model for beef adulterated pork based on synchronous fluorescence technology combined with SVM and PLS has a high recognition rate and detection accuracy, which can accurately and quickly detect whether pork is adulterated in beef.