The Great Xing'an Mountains are an important boreal forest region in China with high frequency of fire occurrences. With climate change,this region may have a substantial change in fire frequency. Building the relationship between spatial pattern of human-caused fire occurrence and its influencing factors,and predicting the spatial patterns of human-caused fires under climate change scenarios are important for fire management and carbon balance in boreal forests. We employed a spatial point pattern model to explore the relationship between the spatial pattern of humancaused fire occurrence and its influencing factors based on a database of historical fire records(1967-2006) in the Great Xing'an Mountains. The fire occurrence time was used as dependent variable. Nine abiotic (annual temperature and precipitation,elevation,aspect,and slope), biotic(vegetation type), and human factors (distance to the nearest road,road density,and distance to the nearest settlement) were selected as explanatory variables. We substituted the climate scenario data (RCP 2.6 and RCP 8.5) for the current climate data to predict the future spatial patterns of human-caused fire occurrence in 2050. Our results showed that the point pattern progress (PPP) model was an effective tool to predict the future relationship between fire occurrence and its spatial covariates. The climatic variables might significantly affect human-caused fire occurrence,while vegetation type,elevation and human variables were important predictors of human-caused fire occurrence. The human-caused fire occurrence probability was expected to increase in the south of the area,and the north and the area along the main roads would also become areas with high humancaused fire occurrence. The human-caused fire occurrence would increase by 72.2% under the RCP 2.6 scenario and by 166.7% under the RCP 8.5 scenario in 2050. Under climate change scenarios, the spatial patterns of human-caused fires were mainly influenced by the climate and human factors.