1. A method for scoring likelihood of success of revised queries suggested for an original query, the method comprising: maintaining log files of user clicks on results provided in response to the revised queries suggested for the original query, the log files including data representing features associated with the original query and the revised queries, and a respective feature value for each feature; selecting a condition, wherein the condition specifies one or more feature values for a corresponding one or more features; selecting the revised queries that, for a particular feature, are associated with a feature value that matches one or more of the feature values specified by the condition for the particular feature; collecting click data for the selected revised queries from the log files, the click data including click length data, wherein a long click on a result for a particular revised query in the log files is taken as indicating a success of the particular revised query; analyzing the click data for the selected revised queries to determine a weight for the condition; formulating a rule by one or more computers, wherein the rule includes the condition and the weight; and adding the rule to a predictive model, wherein the model includes a set of rules that contribute to a prediction of a respective likelihood of success for the revised queries.