Objectives. To investigate the potential association of a set of serum cytokines with the severity of coronary artery disease (CAD). Methods. A total of 201 patients who underwent coronary angiography for chest discomfort were enrolled. The concentrations of serum IFN-γ, TNF-α, IL-2, IL-4, IL-6, IL-10, IL-9, and IL-17 were determined by xMAP multiplex technology. The CAD severity was assessed by Gensini score (GS). Results. The serum levels of TNF-α, IL-6, IL-9, IL-10, and IL-17 were significantly higher in high GS group (GS ≥ 38.5) than those in low GS group (GS < 38.5). Positive correlations were also found between these cytokines and the severity of CAD. After adjustment for other associated factors, three serum cytokines (IL-6, IL-9, and IL-17) and two clinical risk factors (creatinine and LDL-C) were identified as the independent predictors of increased severity of CAD. ROC curve analysis revealed that the logistic regression risk prediction model had a good performance on predicting CAD severity. Conclusions. Combinatorial analysis of serum cytokines (IL-6, IL-9, and IL-17) with clinical risk factors (creatinine and LDL-C) may contribute to the evaluation of the severity of CAD and may help guide the risk stratification of angina patients, especially in primary health facilities and in the catheter lab resource-limited settings.