Background and Aim: Ticks are blood-feeding ectoparasites that transmit pathogens to animals and humans. One of the most important hard ticks in animals is Rhipicephalus microplus, which transmits Babesia and Anaplasma spp. Although many potential tick vaccine candidates have been identified, no effective vaccine that can provide sterile immunity against R. microplus tick infestations has been developed. This study aimed to design a construct using different computational tools to identify and predict immunogenic epitopes within protein sequences and to prepare a messenger RNA (mRNA) vaccine against R. microplus based on lipid nanoparticles (LNPs). Materials and Methods: The R. microplus proteins (Bm86, Subolesin, and ATAQ) were selected and their consensus sequence was obtained from the National Center for Biotechnology Information in FASTA format. The Immune Epitope Database and Analysis Resource (IEBD) server was used for the prediction of helper T-cell epitopes, the NetCTL 1.2 server was used to predict cytotoxic T-cell epitopes, and the ABCpred server was used for B-cell epitope prediction. Antigenicity testing, allergenicity assessment, and toxicity screening were immuno-informatic techniques used to identify potent epitopes within protein sequences. The multi-epitope construct was prepared and cloned into the pVAX1 plasmid. Plasmids were transformed in compatible competent cells, and restriction analysis was performed. After restriction analysis of the transformed plasmid, in vitro transcription was performed to prepare mRNA. The mRNA was purified, quantified, and converted into complementary DNA, and gene-specific primers were used to confirm the in vitro transcription of mRNA. A mixture of four lipids containing 1,2-dioleoyl-3-dimethylammonium-propane (DODAP), Distearoylphosphatidylcholine (DSPC, cholesterol, and 1,2-Dimyristoyl-sn-glycero-3-methoxypolyethylene glycol-2000 (DMG PEG-2000 was used to prepare LNPs. LNPs were characterized using a scanning electron microscope, Zeta potential, and Zeta Sizer tests. Results: More than 1000 epitopes were predicted, from which only nine helper T-lymphocytes, 18 cytotoxic T-lymphocytes, and nine B-cell epitopes of all three proteins were selected with high antigenic scores of 0.958 for Bm86, 0.752 for Subolesin, and 0.964 for ATAQ, respectively. An adjuvant was used to enhance immune responses, all of which were linked to one another using GPGPG, AAY, and KK linkers, respectively. The physiochemical properties predicted that the instability index of the construct would be <40%, indicating that the construct is stable. Plasmids were transformed in compatible competent cells, and white-transformed colonies were observed. Restriction analysis was performed, DNA was transcribed into mRNA, and LNPs were prepared and characterized. Conclusion: More than 1000 epitopes were predicted using immune informatic tools, and only high-scoring epitopes were selected. A multi-epitope construct was designed using bio-informatic tools, and its physicochemical properties were predicted. The design construct was inserted into the pVAX1 plasmid, and in vitro transcription was performed to prepare the mRNA. LNPs of mRNA were prepared and characterized to be used as vaccines. It was found that LNPs were stable and nanometer-sized. Keywords: immuno-informatic tools, lipid nanoparticles, multiepitope construct, Rhipicephalus microplus.