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Episignatures are increasingly valuable for variant interpretation in rare neurodevelopmental disorders, especially when optimized to capture the impact of specific variant types and locations across a gene. Here, we generated a next-generation DNA methylation (DNAm) episignature for Kabuki syndrome type 1 (KS1) using the largest cohort studied to date, aiming to clarify the epigenomic and phenotypic effects of diverse KMT2D variant types and positions. Genome-wide DNAm profiles were obtained for 110 individuals with KMT2D variants and 854 controls using microarrays and long-read sequencing (LRS). Differentially methylated loci were enriched in genes involved in embryonic and nervous system development and were leveraged to construct a support-vector machine classifier for detecting pathogenic KMT2D variants. The classifier achieved 97% sensitivity and 100% specificity in validation cohorts and outperformed in silico tools, demonstrating stronger concordance with clinical presentation. Missense variants in the C-terminal region (exon 48) of KMT2D and the N-terminal plant homeodomain (PHD)-type zinc fingers were predominantly classified as pathogenic, highlighting regions enriched for pathogenic variants. Missense variants in the central region (exons 31-39) were more often predicted benign for KS1, consistent with potential association with a different syndrome, highlighting the classifier's specificity for KS1. Test performance was consistent across array and LRS platforms, and classifier scores reflected levels of mosaicism detected by LRS. The KS1 episignature also positively classified pathogenic KDM6A variants associated with KS2. These findings represent a significant advance in the evolution of episignature development, demonstrating diagnostic and interpretive value of a KS1 signature in resolving uncertain or complex cases.