Objective To investigate the relationship between serum indexes and the degree of liver fibrosis in chronic hepatitis B(CHB)patients with HBeAg-negative and normal ALT,and to establish a new non-invasive model for predicting liver fibrosis in CHB patients.Methods The clinical data of 679 HBeAg-negative chronic HBV infected patients with normal ALT who underwent liver biopsy from October 2012 to December 2021 were retrospectively analyzed.Among these patients,they were categorized into the control group(S1,observation group)the and significant fibrosis group(S2/S3/S4,control group)based on liver biopsy results.The LASSO regression model was used for covariates selection and the restricted cubic splines model was used to examine nonlinear associations between covariates and outcomes.We used Logistic regression models to establish predictive models.Results Liver biopsy showed that 48.7%of the patients had obvious fibrosis(S≥2).GGT shows a nonlinear relationship with the degree of liver fibrosis.AST and PT show a positive relationship with the liver fibrosis degree,respectively.The area under the ROC curve(AUC)of GGT + PT + AST is 0.68(95%CI:0.64～0.72),and this model performed better than models established using GPR,APRI,and FIB-4.Conclusion The prediction model of GGT + PT+AST has high predictive value on the severity of liver fibrosis among CHB patients whose HBeAg is negative.