Abstract
This article examines a number of different approaches to forecasting the demand for new rail stations and services and assesses them in terms of their accuracy and complexity. It is concluded from Revealed Preference (RP) and Stated Preference (SP) surveys that aggregate approaches may be appropriate for cheap investments, such as new stations, or in an initial assessment of a wide range of options. For detailed consideration of expensive investments, such as new rail services, disaggregate methods based on RP and/or SP data should be considered.