OBJECTIVES: H-QoL-I is a quality-of-life indicator specific to the Huntington’s Disease (HD), with 3 dimensions: motor function, psychology and socializing. It has been validated in several countries (France, Italy, Poland, Germany and United States). We compared several methods for mapping H-QoL-I onto EQ-5D and thus derive utility values from H-QoL-I. METHODS: This analysis was based on a sample of 315 HD patients who participated in an international survey on the burden of HD, and completed H-QoL-I and EQ-5D, with help from caregivers if necessary. EQ-5D index scores were calculated based on UK time trade-off tariff. The sample was divided into 70% derivation and 30% validation sets. We compared three methods to estimate patient’s utility as a function of 11 H-QoL-I items: ordinary least-squares (OLS) regression and Tobit regression, with utility score as independent variable, and ordered logistic regression for each item of EQ-5D. Model performance was assessed by comparing predicted and observed mean EQ-5D scores in the validation set, the unadjusted R-squared and the root mean squared error (RMSE). RESULTS: The OLS regression had the best predictive performance with R-squared equal to 0.60 and RMSE equal to 0.25. The linear regression model accurately estimated the mean EQ-5D score in the validation set (predicted score 0.32 versus observed score 0.30).  RMSE values of 0.26 and 0.31 were obtained with Tobit model and ordered logistic model. Items with the greatest contribution to variance in the OLS model were ‘difficulty of tie the laces of my shoes’ (p=0.0018), ‘difficulty to drink without spilling’ (p=0.0156) and ‘difficulty to make precise movements’ (p=0.0165). CONCLUSIONS: EQ-5D utility scores can be reasonably predicted from the H-QoL-I, although item wordings are not directly related. The model based on OLS regression provides the best fitting. Motor functions items contributed the model to utility predictions.