Bacterial plant pathogens rely on a battalion of transcription factors to fine-tune their response to changing environmental conditions and to marshal the genetic resources required for successful pathogenesis. Prediction of transcription factor binding sites (TFBS) represents an important tool for elucidating regulatory networks and has been conducted in multiple genera of plant-pathogenic bacteria for the purpose of better understanding mechanisms of survival and pathogenesis. The major categories of TFBS that have been characterized are reviewed here, with emphasis on in silico methods used for site identification and challenges therein, their applicability to different types of sequence datasets, and insights into mechanisms of virulence and survival that have been gained through binding-site mapping. An improved strategy for establishing E-value cutoffs when using existing models to screen uncharacterized genomes is also discussed.