Objective: To develop a nomogram model for predicting the risk of developing high-normal blood pressure in a health examination population of Chengdu. Methods: A retrospective study was conducted on 1,709 cases of physical examination in the physical examination center of the Third People's Hospital of Chengdu from January 2022 to December 2022. According to the Chinese guidelines for the prevention and treatment of hypertension (2024 revision), the subjects were divided into normal blood pressure group (n=1,152) and high-normal blood pressure group (n=557), and the general information and laboratory test results of the subjects were collected. The receiver operating characteristic (ROC) curve was used to evaluate age, body mass index (BMI), hypersensitive C-reactive protein (hs-CRP), cystatin C (CysC), homocysteine (Hcy), uric acid (UA), triglyceride (TG), total cholesterol (TC), glycosylated hemoglobin (HbA1c), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), fasting blood glucose (FBG) on physical examination of high-normal blood pressure prediction ability and to find the optimal cut-off values. Logistic regression analysis was used to determine the risk factors of high-normal blood pressure in healthy people. The rms (6.4.0) package of R (4.2.1) software was used to construct a nomogram model for predicting the risk of high-normal blood pressure in healthy people. The C statistic and the Hosmer-Lemeshow test were used to evaluate the model's predictive performance and goodness of fit. Results: The detection rate of high-normal blood pressure in healthy people was 32.59% (557/1,709). Multivariate Logistic regression analysis showed that age (OR=1.425, 95%CI:1.137~1.786), gender (OR=1.447, 95%CI:1.063~1.968), BMI (OR=2.958, 95% CI:2.261~3.868) and hematological indexes Hcy (OR=1.614, 95%CI:1.226~2.125), TC (OR=1.383, 95%CI:1.049~1.823) and FBG (OR=1.469, 95% CI:1.164~1.854) were independent risk factors for high-normal blood pressure in healthy people (P<0.05). Hosmer-Lemeshow goodness-of-fit test results showed that the fitting of the nomogram model was better (χ2=11.092, P=0.1965). The ROC curve was drawn on the basis of the model to determine the probability prediction of high-normal blood pressure in the healthy population, with a C-statistic of 0.710 and a 95% CI of 0.684~0.736. The calibration curve analysis showed that the nomogram model predicted the incidence of high-normal blood pressure in healthy people was basically consistent with the actual incidence. Conclusion: Age, gender, BMI and hematological indicators Hcy, TC, FBG are the independent risk factors of high-normal blood pressure in healthy people. The risk prediction nomogram model of high-normal blood pressure in healthy people based on the above factors is well fitted, and has a good degree of differentiation and calibration.