【Objective】Developing forestry carbon sequestration is an important way to address climate change. With the gradual establishment and improvement of China’s carbon markets, forestry carbon sequestration projects have received widespread attention and have good development prospects, but they also face many uncertainties and risks. This study conducted a systematic risk assessment for forestry carbon sequestration projects under the Bayesian network principle and provided a scientific reference for risk management for other projects.【Method】Taking CCER (China certified emission reduction) forestry carbon sequestration projects as the research object, and using expert knowledge form multi-domain forestry carbon sequestration, this study constructed a risk assessment model for forestry carbon sequestration projects based on the Bayesian network by determining the network structure and calculating risk parameters. We combined the information of expert interviews and investigations to determine the risk list, and then determined the Bayesian network structure associated with the risk. We used the entropy weight method to calculate risk factor weight according to the expert’s scoring of the occurrence probability and the impact of various risk factors, so as to obtain the assessment result of each expert on the risk source and the total risk. Finally, all the parameters of the Bayesian network operation were obtained. Using the constructed risk assessment model, we measured the overall risk level of CCER forestry carbon sequestration projects and determined the main risk factors for various risks. Considering the differences in the characteristics of different types of CCER forestry carbon sequestration projects, the risk assessment model was adaptively adjusted by including project-type nodes. This was done to calculate the risk values of four types of CCER forestry carbon sequestration projects through the node probability simulation function of the Bayesian network and to compare the risk diffe-rences of different types of these four projects.【Result】①The overall risk value of CCER forestry carbon sequestration projects was 1.932. Further, the risk levels of the four types from high to low were policy risk, market risk, technical risk, and natural risk, with the corresponding risk values being 2.150, 2.022, 1.925 and 1.546, respectively. ②For CCER forestry carbon sequestration projects, the main risk factors of policy risk were changes in forestry carbon sequestration trading rules and changes in national emission reduction policies. Meanwhile, the main risk factors of market risk included rising labor prices and rising costs of rented land. The main risk factors of technical risk were the projects failing to be issued and the projects failing to be filed; whereas, the main risk factors of natural risk included diseases, pests, and forest fires. ③The risk levels of different types of CCER forestry carbon sequestration projects from high to low were carbon sequestration afforestation project, bamboo afforestation project, forest management project and bamboo forest management project, with risk values of 2.221, 2.121, 1.954 and 1.705, respectively.【Conclusion】The Bayesian network can comprehensively consider both risk level and risk impact information, and had certain advantages in the project risk assessment. The risk level of CCER forestry carbon sequestration projects was medium, and the policy risks and market risks were relatively high under the current conditions. When making investment decisions for forestry carbon sequestration projects, enterprise entities should pay close attention to changes in carbon sequestration market policies and scientifically to evaluate project risks. Relevant departments should focus on reducing systemic risks caused by policy uncertainties, and improve the stability and activity of the carbon sequestration market, as well as simplify the development process of forestry carbon sequestration projects to reduce the transaction costs of the project development.