Duchenne Muscular Dystrophy (DMD) is a severe genetic disorder characterized by progressive muscle degeneration, primarily affecting young boys and leading to significant disability and reduced life expectancy. Mutations in the DMD gene disrupt dystrophin production, triggering a cascade of molecular events that compromise muscle integrity. Despite advances in understanding DMD’s genetic basis, a comprehensive mapping of the molecular networks driving disease progression remains limited. This study addresses this gap through a bioinformatics analysis of gene expression datasets GSE38417 and GSE1004, sourced from the National Institutes of Health Gene Expression Omnibus (NCBI GEO) database. Using the GEO2R tool, we identified 135 differentially expressed genes (DEGs) associated with DMD, revealing distinct patterns of upregulation and downregulation that reflect the disease’s complex pathophysiology. To investigate the interactions among these DEGs, we constructed protein-protein interaction (PPI) networks utilizing the STRING database and Cytoscape software, enabling the identification of 10 hub genes, including SPP1 and POSTN, central to DMD’s molecular architecture. Enrichment analysis, conducted via the Reactome database, associated these hub genes with the extracellular matrix organization pathway, highlighting its essential role in maintaining muscle structure and its dysregulation in DMD. To ensure the robustness of our findings, we validated the DEGs by cross-referencing with data from OMIM and GeneCards, confirming the involvement of these genes and the extracellular matrix organization pathway in DMD pathology. Additional hub genes (e.g., SGCA, SGCD) from OMIM and GeneCards highlighted the importance sarcolemma stability. This study elucidates critical molecular drivers of DMD and underscores potential therapeutic targets, laying a groundwork for future research aimed at mitigating disease progression and enhancing patient outcomes through targeted interventions.