Conventional genetic improvement of disease resistance in aquatic animal species involves challenge tests or using qPCR to quantify viral load that is costly, time-consuming and causing biosecurity concerns. Recent developments in high throughput next generation genome sequencing platforms such as genotyping by sequencing (GBS) have opened new possibilities for improving disease traits based on DNA information. The principal aim of this study was thus to examine potential application of genomic selection to improve resistance to hepatopancreatic parvovirus (HPV) in banana shrimp Fenneropenaeus merguiensis. Specifically, we used a total of 9472 single nucleotide polymorphisms (SNPs) developed de novo from GBS platforms to assess accuracy of genomic prediction for HPV resistance and growth, carcass and quality-related traits in this white shrimp species. Our multi-locus mixed model analysis showed moderate heritabilities for HPV resistance (h2 = 0.46) and other traits studied (0.10 to 0.55). Genetic correlations of HPV titre with growth and carcass traits, estimated using SNPs markers, were negative (i.e., favourable), suggesting that selection for improved growth and carcass traits may have increased HPV resistance (i.e., reduced HPV titre). More importantly, our gBLUP model demonstrated that the accuracy of gBLUP prediction was moderate for HPV disease resistance (0.46). The genomic prediction accuracy was somewhat greater for growth and carcass related traits especially for body weight (0.76) and meat or tail weight (0.77). On the other hand, the prediction accuracy was from 0.25 to 0.41 for quality traits (raw and cooked colour and flesh streaks). Collectively, it is concluded that there are prospects to apply genomic selection in the genetic improvement for increased disease resistance, carcass and quality-related traits in this population of banana shrimp F. merguiensis.