Abstract: Objective　To construct a line graph prediction model for phenotype of acute gastroenteritis in pediatric patients with adenovirus infection and to verify its feasibility. Methods　A total of 144 children infected with adenovirus were selected as the training set, of which 40 (27.8%) showed acute gastroenteritis phenotype and 104 (72.2%) showed respiratory phenotype. The age, sex, days of fever, tonsil exudation, conjunctival congestion, alanine aminotransferase (ALT), aspartate aminotransferase (AST), γ-glutamyltransferase (γ-GT), interleukin (IL-6), lactate dehydrogenase (LDH), percentage of CD4+T cells, CD8+T cells and CD4+cell /CD8+T cell ratio were collected after admission. Predictors of acute gastroenteritis phenotypes were screened using least absolute shrinkage selection (LASSO) regression. Multifactorial Logistic regression analysis was used to establish a risk prediction model to plot column line graphs. Subject working characteristic (ROC) curves and Brier scores were used to evaluate the discriminatory ability and calibration ability of the model, respectively. An additional 35 pediatric patients with adenovirus infection were selected for external validation of the prediction model. Results　Among 144 children infected with adenovirus, 40 cases (27.8%) had acute gastroenteritis phenotype and 104 cases (72.2%) had respiratory phenotype. Compared with the respiratory tract phenotype group, the children in the gastroenteritis phenotype group were younger, with higher proportion of female patients, higher ALT levels, shorter fever days, and lower levels of IL-6 and LDH (P＜0.05). LASSO regression analysis revealed that the age, sex, days of fever and LDH were predictors of acute gastroenteritis phenotype. Multivariate Logistic regression analysis showed that female, young age, short fever time and low LDH were the risk factors of gastroenteritis phenotype of HAdV infection in children. The area under the ROC (AUC) curve of the column diagram model built with the above factors was 0.951 (95%CI: 0.923-0.984), the sensitivity was 82.50%, the specificity was 95.19%. In the external validation set, 8 of the 35 patients had acute gastroenteritis phenotype, the AUC was 0.925 (95%CI: 0.821-0.998), sensitivity was 75.42%, and specificity was 95.90%. Conclusion　The prediction model established in this study is suitable for the early diagnosis of acute gastroenteritis phenotype in children with adenovirus infection, with good prediction effect and certain clinical value.