Analogy-based estimation has, over the last 15 years, and particularly over the last 7 years, emerged as a promising approach with comparable accuracy to, or better than, algorithmic methods in some studies. In addition, it is potentially easier to understand and apply; these two important factors can contribute to the successful adoption of estimation methods within Web development Companies We believe therefore, analogy-based estimation should be examined further. This paper compares several methods of analogy-based effort estimation. In particular, it investigates the use of adaptation rules as a contributing factor to better estimation accuracy. Two datasets are used in the analysis; results show that the best predictions are obtained for the dataset that first, presents a continuous “cost” function, translated as a strong linear relationship between size and effort, and second, is more “unspoiled” in terms of outliers and collinearity. Only one of the two types of adaptat...