CD4-expressing T-cells (CD4Ts) play a crucial role in maintaining the normal functioning of the mammalian immune system and overall systemic health. Diseased individuals, such as those infected with the human immunodeficiency virus type I (HIV-1), experience progressive and eventual depletion of CD4T leading to uncurable conditions and ultimate death if left untreated. Although much is known about the role of CD4T-mediated immunity, the understanding of CD4T-related transcriptomic patterns remains incomplete. This proof-of-concept study aims to identify a transcriptome-wide gene signature for CD4T abundance by Least Absolute Shrinkage and Selection Operator (LASSO) regression modeling in 340 healthy peripheral blood samples. The optimized LASSO model demonstrated computational robustness (tenfold average Pearson’s r = 0.89) and biological relevance evidenced by four significant Gene Ontology terms (all odds ratio [OR] ≥ 4.5 and false discovery rate ≤0.05). Subsequently, in an independent cohort with 24 HIV-1-infected men who received anti-retroviral therapies, there is a significant, positive association between the gene signature and a strong anti-retroviral response before (OR = 13.6, P < 0.05) and after adjusting for subject age, sex, and race (OR = 14.4, P < 0.05). Taken together, the gene expression pattern associated with CD4T abundance is predictable, generalizable, and biologically relevant, shedding new light on the importance of CD4T abundance.