BACKGROUND: Bacterial vaginosis (BV) is the most common vaginal dysbiosis in fertile women, which is associated with side effects including the risk of premature birth. Gardnerella vaginalis (G. vaginalis) is a facultative anaerobic bacillus known as the main pathogen responsible for BV. In this study, using bioinformatics and immunoinformatics methods, a multi-epitope vaccine with optimal population coverage against BV caused by G. vaginalis was designed. METHODS: Amino acid sequences of two important virulence factors (Vaginolysin and Sialidase) of G. vaginalis were retrieved from NCBI and UniProt databases. At first, three online servers ABCpred, BCPREDS and LBtope were used to predict linear B-cell epitopes (BCEs) and IEDB server was used for T cells. Then the antigenicity, toxicity, allergenicity were evaluated using bioinformatics tools. After modeling the three-dimensional (3D) structure of the vaccine by Robetta Server, molecular docking and molecular dynamics were performed. Finally, immune simulation and in silico cloning were considered effective for the design of vaccine production strategy. RESULTS: In total, six epitopes of BCEs, eight epitopes from CD4+ and seven epitopes from CD8+ were selected. The designed multi-epitope vaccine was non-allergenic and non-toxic and showed high levels of antigenicity and immunogenicity. After the 3D structure was predicted, it was refined and validated, which resulted in an optimized model with a Z-score of -7.4. Molecular docking and molecular dynamics simulation of the designed vaccine revealed stable and strong binding interactions. Finally, the results of vaccine immunity simulation showed a significant increase in immunoglobulins, higher levels of IFN-γ and IL-2. CONCLUSION: According to the findings, the candidate multi-epitope vaccine has stable structural features. It also has the potential to stimulate long-term immunity in the host, but wet-lab validation is needed to justify it.