Kidney transplantation outcomes arise from complex interactions among donor organ quality, recipient susceptibility, and immunologic compatibility, yet conventional clinical risk models explain only a modest fraction of outcome variability. Polygenic risk scores (PRS) offer a promising framework to enhance transplant risk assessment by integrating genome-wide genetic information from both donor and recipient into biologically informed models. This narrative review examines the mechanistic basis for PRS application in kidney transplantation and variant clustering approaches that link polygenic signals to specific biological pathways underlying alloimmunity, fibrosis, and metabolic dysfunction. We compare current PRS construction methodologies, highlighting their respective strengths and limitations in transplant cohorts. Transplant PRS are distinguished from single-genome disease models by their capacity to capture dual-genome interactions, simultaneously quantifying inherited donor organ liability and recipient genetic susceptibility within an integrated framework. This dual-genome architecture requires novel risk stratification paradigms in which combined donor-recipient polygenic profiles inform pretransplant decision-making in ways that neither genome alone can achieve. However, current PRS contribute only incremental variance beyond established clinical predictors, and critical limitations persist, including European ancestry bias, small cohort sizes, incomplete replication, and undefined clinical actionability thresholds. We critically evaluate these implementation barriers and outline future directions for integrating dual-genome PRS with clinical, molecular, and environmental data. The longer-term goal is to advance precision kidney transplantation through applications such as donor selection, immunosuppression tailoring, and individualized posttransplant surveillance. Realizing this potential will require validation in adequately powered, ancestry diverse, prospective transplant cohorts.