Percentages of CD4+, CD8+, and CD11b+Gr-1+ cellular biomarkers were assessed by flow cytometry from the peripheral blood of immunized mice, which were subsequently challenged with a high dose of T. cruzi. A machine-learning (ML) model based on decision trees was applied to identify potential CoPs to predict survival by day 25 post-infection. This evidence concerns the gene CD8A and infection.