1. A method for finding predictive cross-category search queries for behavioral targeting, comprising: aggregating, using a computer, at least one training model dataset, the training model dataset comprising at least a history of clicks corresponding to historical advertisement and the training model dataset comprising a plurality of targeting categories; selecting, using a computer, a plurality of features from the at least one training model dataset; and calculating a click probability for a subject advertisement to be clicked by a user from a page, said calculating using at least features of the page and the at least one training model dataset.