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Objective: To identify adenoid inflammatory endotypes based on inflammatory markers, match endotypes to phenotypes, and predict endotypes., Methods: This cross-sectional study included 72 children with adenoid hypertrophy. Thirteen inflammatory markers and total immunoglobulin E (TIgE) in adenoid tissue were analyzed using Luminex and enzyme-linked immunosorbent assay (ELISA) for performing cluster analysis. Correlation analysis was used to examine the characteristics of each cluster. Receiver operating characteristic (ROC) curve analysis was performed to screen for preoperative characteristic data with predictive value for adenoid inflammation endotype., Results: The patients were divided into four clusters. Cluster 1 exhibited non-type 2 signatures with low inflammatory marker concentrations, except for the highest expression of Th1-related cytokines. Cluster 2 showed a non-type 2 endotype with the highest concentration of interleukin (IL)-17A and IL-22. Cluster 3 exhibited moderate type 2 inflammation, with the highest concentration of neutrophil factors. Cluster 4 demonstrated significant type 2 inflammation and moderate neutrophil levels. The proportions of AR and serum TIgE levels increased from clusters 1 to 4, and there was a gradual increase in the prevalence of chronic sinusitis from low to high neutrophilic inflammation. The area under the ROC curve for serum TIgE was higher than those for combined or other separate preoperative characteristics for predicting non-type 2 and type 2 inflammation in the adenoid tissue., Conclusions: The evaluation of cytokines in adenoid tissue revealed four endotypes. Serum TIgE level was an important indicator of the endotype of adenoid inflammation. Identification of adenoid inflammatory endotypes can facilitate targeted treatment decisions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier B.V.)