 This paper presents a novel method for predicting the spatial distribution of braided fluvial fascis reservoirs using probability fusion and multi-point geostatistics. The authors first process similar statistical data from modern sedimentation and field palia outcrops to construct reservoir training images suitable for the target strata in the research area. They then calculate the principal component values of each linear combination of selected seismic attributes and determine the elementary conditional probability of each point. Finally, they use the PR probability integration approach to combine all conditional probabilities and calculate the joint probability. This joint probability is used to build a reservoir distribution model through multi-point geostatistics. The authors tested their method on a braided fluvial reservoir modeling case in the Bohai Bay Basin, East China, and found that the error of prediction results was reduced by 32 percent and 46 percent, and the error of water content was reduced by 36.5 percent and 60.3 percent. This method could be applied to other oil fields with the same geological background. This article was authored by Zhang Xiangkang, Jaogen Ho, Li Qinlu, and others.