Allergic dermatitis (AD) is a common and burdensome inflammatory skin disease, and diagnosis is challenging. This study was conducted to identify candidate genes for AD diagnosis and underlying molecular mechanisms. Gene expression profiles were obtained from datasets GSE121212, GSE130588, and GSE157194. Use differential analysis to identify differentially expressed genes (DEGs) between AD and control. Use enrichment analysis to identify potential molecular dysregulation mechanisms. Comprehensive least absolute shrinkage and selection operator (LASSO) logistic regression, receiver operator characteristic (ROC) curve, and logistic regression analysis are used to identify candidate genes. In addition, ssGSEA and ImmPort database were used to identify AD-related immune response abnormalities. In this study, a total of 60 common genes were identified. Enrichment analysis found that these genes are mainly involved in Th17 cell immune and complement and coagulation cascades. LASSO regression analysis identified 18 feature genes, and screened genes with AUC >0.75 were selected as candidate genes. Finally, PLA2G4D, IFI6, AGR3, IGFL1, SPRR3, ATP13A5, SERPINB13, KRT16, HAS3, and CH25H were recognized as candidate genes and may be able to diagnose AD. PLA2G4D, CH25H, and IFI6 may be risk factors for AD based on logistic analysis. Furthermore, we identified the abnormalities of immune response activation in AD patients. Interestingly, PLA2G4D, CH25H, and IFI6 had positive correlations with immune cells and signaling pathways. PLA2G4D, CH25H, and IFI6 may be candidate diagnostic genes for AD. This may be related to their promotion of abnormal immune activation, especially Th17 cell immune.