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Research into Web cost estimation is relatively new, where few studies have compared cost estimation modelling techniques for Web development, with an emphasis placed on techniques such as Case-based Reasoning (CBR), linear and stepwise regression. Although in a large subset of these studies CBR has given the best predictions, results were based on a simple type of CBR, where no adaptation rules were used to adjust the estimated effort obtained. In addition, when comparing the prediction accuracy of estimation models, analysis has been limited to a maximum of three training/validation sets, which according to recent studies, may lead to untrustworthy results. Since CBR is potentially easier to understand and apply (two important factors to the successful adoption of estimation methods within Web development companies), it should be examined further.This paper has therefore two objectives: i) to further investigate the use of CBR for Web development effort prediction by comparing effort prediction accuracy of several CBR techniques; ii) to compare the effort prediction accuracy of the best CBR technique against stepwise and multiple linear regression, using twenty combinations of training/validation sets. Various measures of effort prediction accuracy were applied.One dataset was used in the estimation process. Stepwise and multiple linear regression showed the best prediction accuracy for the dataset employed.