Image quality assessment for multiply-distorted images is the emphasis and difficulty in image quality assessment (IQA) filed. Based on the high-order phase congruency, a no-reference IQA method for multiply-distorted images is proposed. The high-order phase congruency is computed to capture the structural information of the image. The statistical features of four orders phase congruency are extracted by gray level co-occurrence matrix，respectively. And，based on the analysis of the correlation between adjacent orders of phase congruency and the correlation between adjacent orders of local entropy of phase congruency, the mutual information and cross entropy of that are calculated. The support vector regression is utilized to build a regression model and then it is used for quality predicting. The experimental results on MLIVE and MDID2013 databases show that the proposed method has high consistency with the subjective evaluation scores and outperforms the state-of-the-art full-reference and no-reference IQA metrics.