People who search the World Wide Web often have a multifaceted understanding of their information need: they know what they are searching for, and they know of which form or type the desired documents should be. The former aspect relates to the content of a desired document (= topic), the latter to the presentation of its content and the intended target group. Due to the different user groups and the technical means of the World Wide Web several favorite specializations of Web documents emerged: a document may contain many links (e. g. a link collection), scientific text (e. g. a research article), almost no text but pictures (e. g. an advertisement page), or a short answer to a specific question (e. g. a mail in a help forum). These examples suggest that it can be of much help if the retrieval process is capable to address a user’s information need regarding to—what is called here—“genre” or “Web genre”. This chapter contributes to Web genre analysis. It presents relevant use cases, discusses existing and new technology for the construction of Web genre retrieval models, and outlines implementation aspects for a genreenabled Web search. Special focus is put on the generalization capability of Web genre retrieval models, for which we present new evaluation measures and, for the first time, a quantitative analysis.