In order to prevent land degradation and soil and water pollution, realizing the respective processes and quantifying their relationships is unavoidable. Infiltration process is one of the most important components of the hydrological cycle. On the other hand, the direct measurement of infiltration process is laborious, time consuming and expensive. In this study, the possibility of predicting cumulative infiltration in specific time intervals, using readily available soil data and Pedotransfer Functions (PTFs) was investigated. For this purpose, 210 double ring infiltration data were collected from different regions of Iran. Soil texture ranged from loam to clay. Basic soil properties of the two upper pedogenic horizons including initial water content, bulk density, particle-size distributions, organic carbon, gravel content, CaCO3 percent and soil water contents at field capacity and permanent wilting point were determined on each soil sample. The parametric PTFs were then developed to predict the cumulative infiltration at times 5, 10, 15, 20, 30, 45, 60, 90, 120, 150, 180, 210, 240, 270 minutes after the start of the infiltration test and the time of basic infiltration rate, using the stepwise regression method. The results of reliability test indicated that all derived PTFs underestimated the cumulative infiltration. Also, the obtained RMSEs at small times were lower than those obtained at the ending times of the infiltration process. EF statistic had positive values and increased with time increasing. The EF values indicated that the efficiency of the derived PTFs improved during the time increasing. Also, developed PTFs had a mean RMSD of 6.90 cm in estimating the cumulative infiltration curve. Results indicated that at the 1% probability level, the estimated cumulative infiltration curve can be accepted as one of the replicates of a reliable infiltration test.