An accurate method for locating genes under tumor suppressor p53 control that is based on a well-established mathematical theory and built using naturally occurring, experimentally proven p53 sites is essential in understanding the complete p53 network. We used a molecular information theory approach to create a flexible model for p53 binding. By searching around transcription start sites in human chromosomes 1 and 2, we predicted 16 novel p53 binding sites and experimentally demonstrated that 15 of the 16 (94%) sites were bound by p53. Some were also bound by the related proteins p63 and p73. Thirteen of the adjacent genes were controlled by at least one of the proteins. Eleven of the 16 sites (69%) had not been identified previously. This molecular information theory approach can be extended to any genetic system to predict new sites for DNA-binding proteins.