Abstract Objective To develop and internally validate a model predicting neonatal mortality in infants with neonatal encephalopathy requiring therapeutic hypothermia (TH), using national data. Study design Data from 385 infants treated with TH across 19 hospitals (2016–2021) were analysed. Multivariable logistic regression with backward stepwise selection was applied. Discrimination was assessed using the C-statistic, with internal validation by bootstrapping. The THERM (Therapeutic Hypothermia Early Risk Model for Mortality) tool was developed to calculate individualised mortality risk. Results Forty-six infants (11.9%) died within 28 days. Four predictors were retained: prelabour Caesarean section, adrenaline use, base excess ≤–22 mmol/L, and seizures during the first day of life. The model demonstrated excellent discrimination [optimism-adjusted C-statistic 0.885 (95% CI: 0.827–0.936)]. Conclusions Four routinely collected variables predicted mortality in infants undergoing TH. The THERM tool provides a practical resource for clinicians, enabling personalised risk assessment and supporting parental counselling during the first day of life.