A rapid identification method of microcrystalline cellulose adulteration by near infrared spectroscopy was studied. Based on the near-infrared spectrum data of microcrystalline cellulose samples and adulterants (soluble starch, wheat flour), the material spectrum database and the adulterant spectrum database were created respectively, and the microcrystalline cellulose classification and the adulterant models were also established. A rapid identification method for microcrystalline cellulose adulteration was established by using the Adulterant Screen algorithm technology for calculation and analysis. The minimum detected content of single component adulteration of microcrystalline fiber powder was 2% soluble starch and 1% wheat flour, and the accurate recognition rate was 100%. When the adulteration of two components (soluble starch + wheat flour) was two to ten times of the detection limit concentration of one component, the accurate recognition rate was 100%. The accurate recognition rate of unknown sample microcrystalline cellulose above the detection limit is 100%. The method is simple, rapid and reliable, and can quickly identify adulteration of microcrystalline cellulose samples. It can be effectively applied to the adulteration detection and identification of daily microcrystalline cellulose samples, which could provide technical support for the customs to crack down on tax evasion and evasion.