[Objective] In order to investigate the influencing factors and variation rules of accuracy of various two-step models of 3D mapping methods. [Methods] Soil organic carbon in a forest with an area of about 5 km² in a typical hilly region of South China was mapped. Spline functions, exponential functions and power functions were used as depth functions, ordinary kriging and random forest were used as horizontal mapping methods and two different mapping forms (called forms A and B) were used. The 3D prediction mapping of soil organic carbon was carried out, and the influence of different depth functions, horizontal mapping methods and mapping forms on the 3D mapping results of two-step model was explored. [Results] (1) The depth function largely determined the variation of mapping results in vertical and horizontal directions, which showed that the variation of the mapping results was significantly different among the three depth functions. Exponential function had the largest variation and power function had the weakest variation, while horizontal mapping methods (ie.ordinary kriging and random forest) had little influence on the vertical variation of mapping results. However, the spatial variation of surface layer was greatly affected by the horizontal mapping methods. (2) The accuracy of spline function was the best because the simulated depth curve was in the best agreement with the measured values. The consistency correlation coefficients (CCC) of the 3D mapping based on the spline function were 0.72 and 0.75, which were higher than the other functions in the same form of 3D mapping (CCC were between 0.64 and 0.74). For the horizontal mapping methods, the accuracy of the ordinary kriging was better than that of the random forest, the CCC of the former was between 0.67 and 0.75, the latter was between 0.64 and 0.72; (3) The two mapping forms of the two-step model had little influence on accuracy. Only in the case of prediction for bottom layer, form A (i.e., horizontally mapping simulated walues of a depth function was better than form B (i.e., simulating parameters of a depth function).(4) Among all 3D mapping methods, the form A, with ordinary kriging and spline functions, had the highest accuracy, generating coefficient of determination (R²) of 0.76, CCC of 0.75, and root mean square error (RMSE) of 3.50 g/kg. [Conclusion] In the two-step model of 3D soil mapping, firstly, the spline function should be considered as the depth function. Secondly, the horizontal mapping method should be considered according to the landscape conditions and sample size. Finally, the first mapping form of the two-step model should be adopted as far as possible.