Oropouche virus (OROV) is the pathogen that causes Oropouche fever, an endemic disease in Amazonian regions, whose symptomatology could include complications in the nervous and blood systems, and for which there are no specific treatments or vaccines. The development of vaccines has been supported by advances in areas such as immunoinformatics and the introduction of new vaccination platforms such as viral vectors for the delivery of pathogen antigens. The aim of the present work was to design a vaccine against the Oropouche virus based on a multi-epitope protein and using immunoinformatics. A consensus proteome of OROV was generated from the alignment of sequences stored in databases. Based on this proteome, CD8+ T cell, CD4+ T cell and B cell epitope prediction programs were used to identify peptides with epitope potential. The epitopes to be included in the vaccine were then selected based on the following criteria: high promiscuity towards HLA-I and HLA-II alleles that are prevalent in the countries most affected by the virus, conservation of the peptide among the different OROV strains, non-homology of the peptide with the human proteome, and the absence of toxicity and allergenicity of the peptide. After the filtering and selection process, eleven T cell epitopes, which allowed for a total coverage of the most frequent HLA alleles among OROV-exposed countries, and three B cell epitopes were selected. The chosen epitopes were concatenated by linkers to generate a multi-epitope protein, which also contains the sequence of the β-defensin 3 as an adjuvant. The multi-epitope protein will be evaluated by molecular docking analysis against TLR4 to identify its potential to activate the immune system. This study proposes a vaccine candidate against the Oropouche virus that will be tested in preclinical models in the next phase of this project.