This study investigated the prognostic impact of migrasome-related long noncoding RNAs (lncRNAs) in lung adenocarcinoma (LUAD). We analyzed transcriptomic data from The Cancer Genome Atlas (TCGA) database, comprising 541 tumor samples and 59 normal tissue samples, to pinpoint key migrasome genes and related lncRNAs, using correlation analysis to detect those pertinent to patient outcomes. A risk score model based on 17 migrasome-related lncRNAs, constructed via univariate, LASSO, and multivariate Cox regression, was then validated in an independent dataset to ensure reliability. Our findings revealed that high-risk patients exhibited worse overall and progression-free survival, alongside altered immune features, such as potential immune evasion and an increased propensity for immunotherapy responsiveness. Moreover, Tumor Immune Dysfunction and Exclusion (TIDE) analyses suggested that individuals with higher scores could experience greater benefit from immune checkpoint inhibitors. Functional enrichment analysis supported the engagement of migrasome-related pathways and immune-regulatory processes that may drive disease progression. Additionally, principal component analysis (PCA) confirmed the robustness of our lncRNA-driven classifier, enabling accurate differentiation of risk cohorts. Overall, our study underscores the contribution of migrasome-related lncRNAs in predicting LUAD prognosis and informing clinical choices, shedding light on tumor biology and immunotherapy response. These results emphasize the clinical importance of migrasome-related lncRNAs as promising therapeutic targets and prognostic biomarkers in LUAD management.