Objective:To explore the common risk factors of intracerebral hemorrhage(ICH) in young people and to establish a predictive model of nomogram.Methods:The relevant data of young patients with ICH (≤45 years ) hospitalized in the Department of Neurosurgery of Dezhou people's Hospital from January 2014 to August 2021 were retrospectively studied, and the young group who underwent physical examination in the Physical Examination Center of Dezhou people's Hospital at the same time were randomly selected as the control group. Analyze the risk factors that may affect cerebral hemorrhage in young people, screen the risk factors with statistical differences through single factor analysis, screen the independent risk factors according to multi factor Logistic regression analysis, construct the risk nomogram model of cerebral hemorrhage in young people, and test the efficiency, goodness of fit and benefit of the constructed model through internal validation.Results:Compared with the control group, there were statistically significant differences in family history (χ 2=115.66, P<0.001), hypertension grade( Z=17.67, P<0.001), smoking history (χ 2=33.91, P<0.001), drinking grade ( Z=4.84, P<0.001), body mass index (BMI) ( t=11.76, P<0.001), low density lipoprotein ( t=4.78, P<0.001), high density lipoprotein cholesterol ( t=5.83, P<0.001),blood glucose ( Z=5.68, P<0.001) and homocysteine ( Z=2.22, P<0.001) in the case group. Binary Logistic regression analysis showed that hypertension grade ( OR=3.457, 95%CI: 2.809-4.254, P<0.001), family history ( OR=2.871, 95%CI:1.868-4.413, P<0.001), BMI ( OR=1.093, 95%CI:1.040-1.148, P<0.001), high density lipoprotein cholesterol ( OR=0.230, 95%CI:0.111-0.480, P<0.001), blood glucose ( OR=3.457, 95%CI:2.809-4.254, P<0.001), homocysteine (O R=3.457, 95%CI:2.809-4.254, P<0.001) was an independent risk factor for intracerebral hemorrhage in young adults. The nomogram prediction model showed that BMI was 96 points, hypertension grade was 100 points, family history was 30 points, high density lipoprotein cholesterol was 76 points, homocysteine was 48 points, blood glucose was 52 points,homocysteine was 48 points and blood glucose was 52 points, respectively. The consistency coefficient of the prediction model was 0.874. The nomogram dependent ROC curve AUC was 0.891, and the corresponding sensitivity and specificity were 74.5% (263/353) and 89.7% (437/487), respectively, a nomogram model was established with good diagnostic efficiency. Conclusion:The nomogram model established in this study can predict the probability of intracerebral hemorrhage in high-risk population, and take intervention measures as early as possible to prevent the occurrence of intracerebral hemorrhage in young people.