传统的生存分析方法虽在生物医学领域已有广泛应用，但需满足一些前提假设。随机生存森林方法可克服这一弱点。本文以美国梅奥诊所的肝脏原发性胆汁肝硬化的数据为例，从随机生存森林的原理、建模步骤、实例演示和适用性讨论等方面进行阐述，以期为读者进行生存分析提供新的思路和方法。“,”Traditional survival methods have a wide application in the field of biomedical research. However, applying traditional survival methods requires data to meet a set of special assumptions while the Random Survival Forest model can overcome this inconvenience. Herein, we used the clinical data of Primary Biliary Cholangitis (PBC) from Mayo Clinic to introduce and demonstrate Random Survival Forest model from mathematical principles, model building, practical example and attentions, aiming to provide a novel method for doing survival analysis.