DNA methylation (DNAm) is one of the most important epigenetic event effecting gene expression, and aberrant DNAm has been implicated in the initiation and progression of human cancers. To identify methylation (ME) signature genes for the pathogenesis of lung squamous cell carcinoma (LUSC), the pattern recognition method was used to analyze the genome-wide gene ME data, which were collected from the LUSC normal and cancer stage I samples in The Cancer Genome Atlas project database. A total of 102 ME signature genes were identified by means of a combination of statistical methods such as correlation, analysis of variance, and Elastic Net. The accuracy and specificity are all above 99%, sensitivity is 100%, and Matthews correlation coefficient is higher than 0.99 through the machine learning method modeling, which are higher than the previous study. The Kyoto Encyclopedia of Genes and Genomes pathway analysis and Gene Ontology enrichment analysis indicated the highly related relationship among these genes. They also indicated the immediate relationship between our signature genes and the occurrence of LUSC, which is very important to the understanding of its mechanism and to the development of new targeted therapy.