A stochastic model based on Markov random field is proposed to model the spatial distribution of vehicle loads on longspan bridges. The bridge deck is divided into a finite set of discrete grid cells, each cell has two states according to whether the cell is occupied by the heavy vehicle load or not, then a four-neighbor lattice-structured undirected graphical model with each node corresponding to a cell state variable is proposed to model the location distribution of heavy vehicle loads on the bridge deck. The node potential is defined to quantitatively describe the randomness of node state, and the edge potential is defined to quantitatively describe the correlation of the connected node pair. The junction tree algorithm is employed to obtain the systematic solutions of inference problems of the graphical model. A marked random variable is assigned to each node to represent the amplitude of the total weight of vehicle applied on the corresponding cell of the bridge deck. The rationality of the model is validated by a Monte Carlo simulation of a learned model based on monitored data of a cable-stayed bridge.