This paper presents a new estimation model to consider the effect of initial dry density on the soil–water characteristic curve (SWCC) of granular soils. The proposed method is based on the Fredlund and Xing equation without increasing the number of adjustable parameters. The experimental data from a soil database is partitioned into two groups for fitting and verification of the proposed method. From the verification results, it can be seen that the proposed method provides significantly better estimation of SWCC for the granular soils with different initial dry densities than the Fredlund and Xing equation. From the comparison and statistical analysis, it is found that the estimations by the present method exhibit higher correlations with experimental data than the Tarantino's model for the granular soil samples. The uncertainty of measurement data is analyzed by using the Bayesian method and applied in the estimation of the relative permeability function (kr). Different levels of confidence intervals ofSWCC are obtained by the Bayesian approach. It is found that the proposed method can better predict the kr valueswith smaller uncertainty for the soilwith different initial dry densities than the Fredlund and Xing equation. The new method is readily adopted for engineers to quickly estimate the SWCC and relative permeability of granular soil under different initial dry densities.