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Microbial flora and microorganism metabolites in vinegar culture are the key factors influencing Zhenjiang vinegar unique taste and flavor. Studying the rapid identification of microorganism is uniquely conducive to monitor community composition and dynamic changes and guarantee the quality of vinegar. Rapid identification of five similar bacilli was acquired using near-infrared spectra. Firstly, 120 spectra from five common bacilli (each common bacillus had 24 spectra) were obtained by near-infrared, and PCR was applied to identify the microorganism of five bacilli (namely Baclicus lincheniformis , Bacillus pumilus, Lactobacillus acidophilus, Acetobacterium balch and Bacillus subtilis ). Simultaneously, KNN and LS-SVM were employed to establish identification model of five kinds of common bacilli. Results indicated that the best predictive precision of KNN model can be reached when principal component signals were four and parameter K was three, and precision rates of calibration set and prediction set were 86.25% and 85.00%, respectively. The precision rates of calibration set and prediction set were 100% and 97.50%, respectively, in LS-SVM model provided the principal component signals were four. There was non-linear correlation between near-infrared spectrum and characteristic of bacillus, and the prediction and precision of LS-SVM identification would be better. The research results laid the basis for rapid monitoring of microbial community and dynamic changes.