Abstract: Based on the random generate-growth method, a theoretical method employing linked lists was implemented to predict the effective thermal conductivity of fiber-reinforced composite materials with random structure, which has the feature of physical intuition and independent of mesh. The fiber perform of like-PICA (Phenolic impregnated carbon ablator) was studied to reveal the relevant factors that can influence the effective thermal conductivity. The results show that the effective thermal conductivity is not an intrinsic property and it may be related with the specimen size when it is close to fiber length. There is a positive nonlinear correlation between the fiber quantity per volume and the effective thermal conductivity. However, the effective thermal conductivity is not a uni-variate function of volume fraction and the concept of the effective length is present to describe the connectivity of fiber perform, which is negative correlation with the effective thermal conductivity.