A hardware Trojan detection model based on PCA and Logistics Regression is proposed to promote the performance of detection of IC planted with hardware Trojan. PCA is used to analyze the collected side channel power signals to combine and select main features, remove the affection of noise, and simplify the computation. Logistics Regression algorithm is adopted to train the classifier. The hardware Trojan is detected by calculating the logarithm of ratio between probabilities of including Trojan and excluding Trojan. The FPGA experiment platform is designed and established to validate the proposed model. Two indicators (precision and recall) are used to evaluate the model’s performance. Experiment results show that this model can be used to detect hardware Trojan effectively.