Zika virus infection is primarily caused by the bite of infected Aedes aegypti mosquitoes. Most Zika infections are either asymptomatic or result in mild symptoms. However, if a pregnant woman is infected, it can lead to severe outcomes such as microcephaly, neurological disorders, and impaired development in the baby. Despite the urgency, there is currently no specific treatment or approved vaccine for Zika virus. Therefore, developing an efficient therapeutic is imperative. This study aims to identify potential miRNA-based therapeutics against Zika virus using computational biology approaches. We employed our developed webserver, miRNAProtPred, to predict human miRNAs targeting the 3'UTR and polyprotein sequences of the Zika virus. We compiled a list of experimentally reported downregulated miRNAs and upregulated genes during Zika infection from various literature sources. Subsequently, we identified miRNAs that were common between the experimental data and our predictions. Additionally, we performed miRNA/gene interaction analysis and pathway analysis. Our results revealed 105 miRNAs and 72 genes that are experimentally reported as downregulated and upregulated during Zika infection, respectively. Notably, several predicted miRNAs, such as hsa-miR-124-3p, hsa-miR-762, hsa-miR-6071, and hsa-miR-431-5p, were identified as potential inhibitors of Zika virus replication and protein expression. Furthermore, pathway analysis highlighted multiple pathways associated with viral infection, including viral processes, apoptosis, NF-κB signaling, MAPK signaling, and others. These findings support the reliability of our approach and the potential of the predicted miRNAs to control Zika virus growth. However, further experimental validation is required before progressing to different stages of clinical trials. The current approach will facilitate the development of miRNA-based therapeutics against various pathogenic diseases.