This study aimed to build a soil hydraulic properties digital database and to identify predictors for soil water retention of Inceptisols using data from developed database. Soil survey reports were compiled and soil hydraulic properties were entried into a spreadsheet. As many as 230 datasets of Inceptisols were extracted from developed database to identify predictors for soil water retention using Banin-Amiel and Stepwise techniques. Currently, the Soil Hydroulic Properties Digital Database strores 832 datasets from Central Kalimantan, East Kalimantan, Flores Island, Lombok Island, and Gorontalo District. The dataset is dominated by Inceptisols and fine soils. The correlation between soil water retention and other soil properties, and the order of predicting effectiveness varies with matrix potensial (pF) which influenced by soil moisture regime and pedogenesis type. Total pores and cation exchange capacity are potential predictors for soil water retention of Inceptisols in addition to particle sizedistribution, organic carbon, and bulk density. The Soil Hydraulic Properties Digital Database stores research results and provides data for any study regarding soil hydraulic properties. The dataset selection for developing pedotransfer function of Inceptisols should consider both soil moisture regime and pedogenesis type.