More than half of the global population is affected by the gram-negative bacterium, Helicobacter pylori. The bacterium’s diversity and its mechanisms for evading the immune response pose significant challenges for vaccine development. However, recent advances in bioinformatics and computational vaccine design have provided tools that may facilitate this process. In this study, a multi-epitope vaccine was designed for Helicobacter pylori using in silico methods. The FlaA and UreB proteins were initially selected as they are known to be highly antigenic, essential for bacterial function, and less variable than other candidates. Epitopes were predicted and evaluated using state-of-the-art tools, and a vaccine candidate was designed using protein engineering techniques. The final candidate was then assessed using molecular docking simulations. The results indicate that the construct exhibits strong binding capabilities with immune system components, making it a promising candidate for further studies.