Background and aims: The model for end stage liver disease (MELD) and its sodium-corrected variant (MELD-Na) have created gender disparities in accessing liver transplantation (LT). We derived and validated a new model that replaced creatinine with the Royal Free glomerular filtration rate (PMID: 27779785) within the MELD and MELD-Na formulas. Method: The “Gender-Equity Model for liver Allocation” (GEMA) and its sodium-corrected variant (GEMA-Na) were trained and internally validated in adults listed for LT in the United Kingdom (2010–2020) using generalized additive multivariate Cox regression. The models were externally validated in an Australian cohort (1998–2020). The primary outcome was mortality or delisting due to clinical deterior- ation at 90 days. The Greenwood-Nam-D’Agostino test was used to test calibration. Results: The study comprised 9, 320 patients: 5, 762 patients for model training, 1, 920 patients for internal validation, and 1, 638 patients for external validation. The prevalence of the primary outcome ranged from 5.3% to 6%. In the internal validation cohort, GEMA and GEMA-Na showed a Harrell’s c-statistic = 0.752 and 0.766, respectively, for the primary outcome, which were significantly higher than those of the MELD score (0.712) and the MELD-Na score (0.742). Results were consistent in the external validation cohort. Among women, these differences were more pronounced (see Harrell’s c-statistics in the table). GEMA and GEMA-Na were adequately calibrated and prioritized differently 43.9% and 41.8% of LT patients, respectively. Patients prioritized by GEMA-Na were more often women, had higher prevalence of ascites and showed triple risk of the primary outcome compared to patients prioritized by MELD- Na. One in 15 deaths would be avoided by using GEMA instead of MELD, and 1 in 21 deaths would be avoided by using GEMA-Na instead of MELD-Na. Among women, 1 in 8 deaths would be avoided in either situation. Conclusion: GEMA-Na predicts mortality or delisting due to clinical deterioration in patients awaiting LT more accurately than MELD-Na and its implementation may amend gender disparities.