REACH (Registration, Evaluation and Authorization of CHemicals) requires improved exposure models that can be incorporated into screening tools and refined assessment tools. These are referred to as tier 1 and 2 models, respectively. There are a number of candidate in tier 1 models that could be used with REACH. Tier 2 models, producing robust and realistic exposure assessments, are currently not available. A research programme is proposed in this paper that will result in a new, advanced exposure assessment tool for REACH. In addition, issues related to variability and uncertainty are discussed briefly, and some examples of tier 1 screening tools are presented. The proposed framework for the tier 2 tool is based on a Bayesian approach, and makes full use of mechanistically modelled estimates and any relevant measurements of exposure. The new approach will preclude the necessity to conduct of case-by-case exposure measurements for each chemical and scenario, since the system will allow for the use of analogous exposure data from relatively comparable scenarios. The development of the new approach requires substantial effort in the area of mechanistic modelling, database development and Bayesian statistical techniques. In this paper, the data gaps and areas for future research are identified to help realise and further improve this type of approach within REACH. A structured data collection and storage system is a central element of the research programme and the availability of this type of tool may also facilitate the sharing of exposure data down and up the supply chain. In addition, new data that are stored according to the proposed structure could enable the validation of any exposure model and thus this programme enhances the exposure assessment field as a whole.