Temporal and spatial soil variabilities reduce the accuracy of quantifying the hydraulic properties of the soil, leading to poor irrigation management. Modeling estimation and computer codes (e.g., RETC code) have been used to quantify and predict soil hydraulic properties. One hundred soil samples were collected to represent soil textural classes according to USDA textural triangle. Following the physical, chemical and hydraulic characterization of the soil samples collected, one soil sample was chosen to represent each texture class. The selected soil samples covered six USDA textural classes. Then, Brooks-Corey (B-C) (1964) and van Genuchten (vG) (1980) parametric models were used to describe the functional relationship between soil water tension and water content, i.e. the soil water retention curve, and the Mualem (1976) theoretical models of pore size distribution were used to predict the functions of unsaturated conductivity K (θ) and soil water diffusivity D (θ). The RETC (retention curve) code was used to obtain the parameters of vG and B-C models by simultaneously matching to the observed data. Output file of refining process showed the iteration levels to achieve minimum value of residual summed square (RSSQ).The values of determination coefficient (R2) of the fitted θ (h) as a power function increased after fitting the experimental data either in B-C or in vG models. The values of R2 of the fitted equation of θ (h) with both B-C and vG data increased after refining process through RETC code. The increments of R2 values after refining are more pronounced in coarse textured samples (Sand, Loamy sand, and Sandy loam).The values of determination coefficient (R2) of the fitted functions K (θ) and D (θ) as a power function are highly significant after fitting soil parameters either in B-C or in vG models. While using RETC code refined the obtained soil parameters of both K (θ) and D(θ) increasing R2 values of fitted power function and reducing residual summation square. RETC reduced the value of residual summed square (RSSQ) of the objective function O(b) under using both B-C and vG models. This reduction of RSSQ by using RETC fluctuated between 60.4% and 98.2% with B-C for six soil textural classes. While, the reduction of RSSQ by using RETC fluctuated between 90.4% and 98.6% with vG for the same six soil textural classes. In general, the RETC code is a good tool for obtaining accurate values of hydraulic properties in a variety of soil textures.