Food consumption data is a key element of EFSA’s risk assessment activities, forming the basis of dietary exposure assessment at the European level. In 2011, EFSA released the Comprehensive European Food Consumption Database, gathering detailed consumption data from 34 national food consumption surveys representing 66,492 individuals from 22 EU Member States. Due to different survey methodologies used, national survey data cannot be combined to generate average European estimates of dietary exposure. Although the EU menu project, which aims to collect harmonised food consumption data at EU level, will address this limitation of the Comprehensive database, data from this project will not be available until 2018. The present methodological study was executed to assess how the compatibility or existing consumption data as well as the representativeness of food dietary exposure and risk estimates at the European level could be improved through the development of a “Compiled European Food Consumption Database To create Such a dat abase, the usual intake distributions of 589 food items representing the total diet were estimated for 36 clusters, each one composed of subjects belonging to the same age class (children, adolescents or adults). gender and having a similar diet. An adapted form of the NCI (National Cancer Institute) method was used for this, with a number of important modifications. Season, body weight and whether or not the food was consumed at the weekend were used to predict the probability of consumption. Additionally, the gamma distribution was found to be more suitable for modelling the distribution of food amounts n the different food groups instead f the normal distribution. These distributions were combined with food correlation matrices according to the Iman and Conover method in order to simulate 28 days of consumption for 40,000 simulated individuals. The simulated data were validated by comparing the consumption statistics (e.g. mean, median and certain percentiles) of the simulated individuals to the same statistics estimated from the observed individuals of the Comprehensive Database. The same comparison was done at food group level for each cluster. The opportunities and limitations of using the simulated database for exposure assessments are described.