An AdaBoost.M2-NFS model was presented to improve the recognition rate of traditional Neural Fuzzy System (NFS) towards similar plants. The traditional NFS was improved for fusion, and then the new NFS was combined with AdaBoost.M2 to get a new AdaBoost.M2-NFS model. Experimental results show that the new model increases the recognition rate by 3.33 percentage points compared with the single NFS; compared with the linear Support Vector Machine (SVM), its recognition rate increases by 1.11 percentage points; compared with Softmax, its recognition rate increases by 3.33 percentage points. Based on sensitivity and specificity analysis, the non-linear data can get better classification result than the linear data by the proposed algorithm. At the same time, due to the improvement of AdaBoost.M2, the new algorithm has the advantages of modeling quickly and high generalization ability in the field of plant recognition.