In this paper, we constructed prediction models for overall survival by random survival forest (RSF) [17], a nonparametric method shown to be robust for covariates with nonlinear effects and complex interactions in modeling time-to-event data [18–20], to evaluate the value of CEA, CA19-9, and CA125 on CRC prognostic assessment more intuitively. The gene discussed is CEACAM5; the disease is colorectal carcinoma.