Background: We tested the hypothesis that candidate genetic variants are associated with cognitive impairment in BMT recipients for HM, and that inclusion of genetic variants improves the performance of a risk prediction model that includes only clinical and demographic characteristics. Methods: We used standardized tests to assess cognitive function in 277 adult BMT recipients at City of Hope (COH). Global Deficit Score (GDS) ≥0.50 was used as indicator of cognitive impairment. Generalized estimating equation models and logic regression were used to identify single-SNP and gene-level associations with cognitive impairment post-BMT. Three risk prediction models were developed in the COH cohort using elastic net regression: Base Model (sociodemographics); Clinical Model (Base Model + clinical characteristics, therapeutic exposures and baseline cognitive reserve); Combined Model (Clinical + Genetic Model). The Genetic Model included significant SNPs in blood brain barrier, telomere homeostasis and DNA repair identified from single- and gene-level analyses. Models were validated in an independent cohort of long-term BMT survivors (BMTSS) with (n = 141) and without (n = 258) memory problems. Results:Training set (COH): The cohort included 58.5% males; 68.6% non-Hispanic whites; 46.6% allogeneic BMT recipients; median age at BMT: 51.6y. The mean area under the receiver operating characteristic curve (AUC) was: Base Model: 0.69 (95%CI: 0.63-0.75); Clinical Model: 0.77 (95%CI: 0.71-0.83); Combined Model: 0.89 (95%CI: 0.84-0.92). Test set (BMTSS): Median age at BMT was 45y; 53.5% were males; 88.4% non-Hispanic whites. Testing the models in BMTSS yielded mean AUC of 0.57 (95%CI: 0.49-0.63) in the Clinical Model and 0.72, (95%CI: 0.65-0.78) in the Combined Model. Conclusions: These findings provide evidence on the utility of a validated risk prediction tool that incorporates genetic factors that could identify BMT recipients at risk for cognitive impairment, providing opportunities for targeted interventions.