Abstract: Objective To analyze the contributing risk factors of carotid plaque in people with high-normal blood pressure. Methods A total of 10 455 subjects with high-normal blood pressure were retrospectively selected in people who underwent a physical examination at the health management center of The First Affiliated Hospital of Zhengzhou University from January 2017 to December 2019. The subjects were subsequently divided into carotid plaque group（n=4 584） and normal carotid artery group（n=5 871） according to the results of carotid arteries ultrasound. Gender, age, body mass index（BMI）, waist circumference, and blood biochemical indicators were compared between the two groups. Logistic regression was used to analyze the contributing risk factors of carotid plaque. Nomogram was applied to visualize the contributing factors. Receiver operating characteristic（ROC） curve was used to evaluate the efficiency of the nomogram model to predict carotid plaque. Results Compared with the normal carotid artery group, subjects in the carotid plaque group were more likely to be males, older, with higher BMI, fasting blood glucose, blood pressure, low density lipoprotein cholesterol（LDL-C）, creatinine and urea nitrogen, and lower glomerular filtration rate（all P＜0.05）. Univariate logistic regression analysis showed that male, increased age, fasting blood glucose, total cholesterol and LDL-C were risk factors for carotid plaque（all P＜0.05）. Multivariate logistic regression analysis（forward stepwise） showed that male（OR=1.81, 95%CI 1.63-2.02）, age（compared with age 18-＜40 years, 40-＜50 years, OR=3.77, 95%CI 3.01-4.74; 50-＜60, OR=8.82, 95%CI 7.06-11.02; 60-＜70, OR=17.96, 95%CI 14.13-22.84; ≥70, OR=27.84, 95%CI 20.30-38.18）, fasting plasma glucose≥7.0 mmol/L（compared with ＜6.1 mmol/L, OR=1.56, 95%CI 1.34-1.82） and increased LDL-C（OR=1.26, 95%CI 1.15-1.38） were independent risk factors for carotid plaque in people with high-normal blood pressure（all P＜0.05）. The risk prediction model was established based on the four independent risk factors, with good accuracy and discrimination（C-index=0.707, 95%CI 0.699-0.717）. ROC curve analysis for prediction model showed that the area under the curve（AUC） was 0.707（95%CI 0.697-0.717）, sensitivity was 71.1% and specificity was 59.6%. Conclusions Male, age, increased fasting plasma glucose and LDL-C level are significantly associated with carotid plaque in people with high-normal blood pressure, and the carotid plaque risk prediction model based on these risk factors can help to identify the high-risk populations.