Ovarian cancer (OC) is one of the most pervasive malignancies in women and is recognized for its high recurrence and metastasis rates, resulting in a poor prognosis. Regrettably, reliable indicators for the timely detection and prognosis of OC are currently insufficient. Our research aimed to evaluate the immune therapeutic and prognostic possibilities of laminin α5 (LAMA5) in OC using bioinformatics analysis. LAMA5 expression and clinical features were analyzed in OC tissues using TCGA and GEO databases. Cox and LASSO analyzes were utilized for the identification of genes with differential expression, leading to the development of a prognostic model centered around LAMA5. Time-based receiver operating characteristic curves were examined to assess the nomogram's accuracy. Furthermore, we explored the correlation between risk score and tumor mutational burden (TMB), infiltration of immune cells, immune response, and chemotherapy. A signaling pathway analysis was performed to determine the associations between our findings. Immunohistochemical (IHC) analysis was conducted to validate the prognostic significance of LAMA5. Our study demonstrated that LAMA5 was overexpressed in OC patients. According to the Kaplan-Meier survival analysis, the patients with low LAMA5 expression exhibited a significantly higher survival rate compared to those with high LAMA5 expression, indicating a negative impact on the overall prognosis. Additionally, LAMA5 can serve as a distinct prognostic determinant. We developed a sophisticated predictive model that integrated six genes with distinct expression patterns. A clear correlation was found between the predictive model and TMB, immune cell infiltration, as well as the efficacy of immunotherapy and chemotherapy. IHC revealed that LAMA5 protein expression was significantly increased in OC tissues. An increased expression of LAMA5 was associated with an unfavourable outcome in relation to OS and PFS in patients. This study offers novel perspectives on immunotherapy for OC by demonstrating the reliability of a prognostic model based on LAMA5 in predicting patient outcomes. Our risk model holds promise as an efficient biomarker for enhancing prognostic prediction accuracy and facilitating personalized treatment strategies for OC patients.