The security level of Internet of Things devices is generally low, which has caused many hidden safety hazards. The IoT botnet is one of them. In response to the above problems, an IoT botnet detection model based on RF-RFECV and LightGBM is designed. The model used RF-RFECV to select features according to the importance of features, and used LightGBM to build the model. The experimental results show that this model is improved to a certain extent compared with the traditional detection algorithm in accuracy, precision, recall rate and F1 score, which is useful for future IoT botnet research.