Predicting query performance (PQP) has recently been recognized by the IR (information retrieval) community as an important capability for IR systems. In recent years, research work carried out by many groups has confirmed that predicting query performance is a good method to figure out the robustness problem of the IR system and useful to give feedback to users, search engines and database creators. In this paper, the basic predicting query performance approaches for text retrieval are surveyed. The data for experiments and the methods for evaluation are introduced, the contributions of different factors to overall retrieval variability across queries are presented, the main PQP approaches are described from Pre-Retrieval to Post-Retrieval aspects, and some applications of PQP are presented. Finally, several primary challenges and open issues in PQP are summarized.