The invention discloses a Bayesian network-based regional heat supply model predictive control system and method. The method includes the following steps that: step S1, physical layer heat network data sensing is performed: historical data are acquired from a source side, a network side and a building side in real time and are updated; step S2, a Bayesian network is constructed according to the historical data and on the basis of prior knowledge, and the load demand of a thermal station and the building side are predicted through the Bayesian network; step S3, the real-time control parametersof a secondary side, a primary side and the source side are obtained through the inference of the Bayesian network according to the load demand of the building side and on the basis of the historicaloperation data and real-time data; and step S4, time characteristic curves of source side adjustment, network side adjustment and building side adjustment are established according to the historical operation data and pipe network topology structures, and source side adjustment, network side valve and building side electric valve adjustment strategies are determined, control operations are performed according to the strategies, so that the hysteresis of heat network adjustment can be eliminated, real-time supply and demand balance can be met, and the accurate on-demand heat supply of a heat user side can be realized.