Immune and inflammatory responses are important in the occurrence and development of periodontitis. The aim of this study was to screen for immune-related genes and construct a disease diagnostic model to further investigate the underlying molecular mechanisms of periodontitis.GSE16134 and GSE10334 datasets were used in this study. Differentially expressed genes (DEGs) between the periodontitis and control groups were selected. Immune-related genes were identified, and functional analysis and construction of an interaction network were conducted. Immune characteristics were evaluated using gene set variation analysis GSVA. Immunity-related modules were analyzed using weighted gene co-expression network analysis (WGCNA). The LASSO algorithm was applied to optimize the module genes. Correlation between optimized immune-related DEGs and immune cells was analyzed.A total of 324 immune-related DEGs enriched in immune- and inflammation-related functions and pathways were identified. Of which, 23 immune cells were significantly different between the periodontitis and control groups. Nine optimal immune-related genes were selected using the WGCNA and LASSO algorithms to construct a diagnostic model. Except for CXCL1, the other eight genes were significantly positively correlated with regulatory T cells, immature B cells, activated B cells, and myeloid-derived suppressor cells.This study identified nine immune-related genes and developed a diagnostic model for periodontitis.© 2023. The Author(s).