DNA methylation is a key epigenetic alteration in tumorigenesis, but its diagnostic value in early-stage lung cancer remains unclear. In this study, tissue and plasma samples from patients with lung cancer or benignity were analyzed. Methylation profiles were obtained using bisulfite sequencing and compared with selected lung cancer-specific markers. Diagnostic prediction models were constructed using these markers, with their efficacy assessed by sensitivity, specificity and area under the curve (AUC). In the tissue cohort, 276 markers were found to be significantly differentially methylated in lung cancer (FDR < 0.05). A diagnostic prediction model using six markers showed promising performance in both the training cohort (sensitivity = 90%; specificity = 97%; AUC = 0.988) and the validation cohort (sensitivity = 92%; specificity = 94%; AUC = 0.977). In the plasma cohort, a diagnostic prediction model using nine markers achieved a sensitivity of 98% and specificity of 100% (AUC = 0.998) in the training cohort, a sensitivity of 81% and specificity of 59% (AUC = 0.791) in the validation cohort. Furthermore, we observed a significant correlation between delta methylation changes in tissue and plasma in the paired patient cohort. Additional analysis based on methylation haplotypes identified 1222 differentially methylated regions in tissue samples, mainly enriched in DNA replication-related pathways. Additionally, correlations between DNA methylation and clinical characteristics revealed significant differential methylation patterns between smokers and non-smokers . Thus, DNA methylation in both tissue and plasma holds potential as a biomarker for the early diagnosis of lung cancer.