Abstract: This study uses spatial statistical methods to investigate spatial relationship between ore deposits and fractures in Liaoning Province of China. Firstly, Ripley's K-function and bivariate J function find that the ore deposits have a clustering trend around the fractures. Secondly, a conditional intensity formula for ore deposits based on Poisson process is used to model the ore deposits' spatial dependence on the fractures, and the formula of model is fitted in statistics software called R. Finally, the fitted model is used to predict high intensity areas of invisible ore deposits based on locations of visible fractures, which could be used to guide ore deposit exploration.