Background <p>Lung adenocarcinoma (LUAD) is a highly heterogeneous disease, bringing daunting challenges in prognosis prediction. Alterations in mitochondrial dynamics (MD) are crucial in tumor generation and progression. Therefore, this study is the first to build a prognostic model based on mitochondrial dynamics-related genes (MDRGs) to predict microenvironment and potential drugs for LUAD.</p> Methods <p>LUAD transcriptomic data were sourced from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO), respectively. First, differentially expressed genes (DEGs) were screened between normal and LUAD samples in the TCGA cohort. The intersection of DEGs and MDRGs yielded differentially expressed MDRGs (DE-MDRGs). Then, a prognostic model was constructed through univariate Cox regression, LASSO Cox regression, and multivariate Cox regression analysis. A nomogram was graphed using clinical factors and the MD-related risk score (MDRS). The predictive performance of the model and the nomogram was evaluated using ROC curves. Finally, analyses on tumor microenvironment (TME), mutation, and predicted in vitro drug response were undertaken.</p> Results <p>A prognostic model based on 8 MDRGs (SLC52A3, HMGA2, CPS1, GLS2, CYP27A1, CFTR, STAR, and DRP2) was established, demonstrating relatively accurate predictive ability. The low-MDRS group had higher levels of immune cell infiltration, such as aDCs, B cells, neutrophils, and tumor-infiltrating lymphocytes. We also discovered that the tumor mutation burden in the high-MDRS group was considerably higher than that in the low-MDRS group. Additionally, the low-MDRS group was more sensitive to AZD8055, ZM447439, ERK-6604, SB505124, Tozasertib, and BMS-754807, while the high-MDRS group was more sensitive to BI-2536 and Venetoclax.</p> Conclusion <p>This work set up a prognostic model for LUAD based on 8 MDRGs, pinpointing promising biomarkers and targets for LUAD treatment.</p>