Abstract: The interference identification and classification of wireless sensor networks are important problems to improve network performance. To solve such problems, methods for interference identification and classification were designed and implemented. The experimental transmission parameters of the sensor network nodes were obtained in different interference state, and then the Logistic model was used to identify the state of interference and classify the type of the interference based on the parameters given. The actual network data tests show that the classification model in the identification accuracy can be achieved more than 97%, which can effectively address the problem of recognition of network interference.