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Banana bract mosaic virus (BBrMV) is the most economically damaging and deleterious Potyvirus pathogen (family, Potyviridae) of banana (2n = 3x = 33) that causes significant losses to banana production Asia. The BBrMV has a single-stranded, positive sense ssRNA genome of 9708 nucleotides. RNA interference (RNAi) is an evolutionarily conserved biological potent intracellular response mechanism in eukaryotic organisms and is an antagonist of virus replication. The current study focuses on the role of banana genome-encoded microRNAs (mac-miRNAs) targeting +ssRNA genome of the BBrMV using in-silico predictive algorithms, RNA22, RNAhybrid, TAPIR and psRNATarget. Mature banana locus-derived mac-miRNA sequences (n = 32) were tested for alignment with the BBrMV genomic +ssRNA (NCBI accession No. MG758140). In total we extrapolated 32 mature banana miRNAs, only two of which are potentially efficient miRNAs (mac-miR157b and mbg-miR397a) to have high-affinity target sites in the BBrMV genome. To identify emerging therapeutic targets, we utilized Circos software to develop a network illustrating potential mechanistic RNA-RNA interactions, based on robust prediction algorithms. Our findings provide the first in silico evidence of multiple dynamic tenacious interaction between banana high-confidence miRNAs and Potyvirus genome. This work represents a critical step towards proactive biosecurity preparedness, offering a predictive framework for engineering BBrMV-resistant banana plants and safeguarding domestic banana production.