The aim of probabilistic models is to define a retrieval strategy within which documents can be optimally ranked according to their relevance probability, with respect to a given request. In this scheme, the underlying probabilities are estimated according to a history of past queries along with their relevance judgments. Having evolved over the last twenty years, these estimations allow us to take both document frequency and within-document frequency into account.