One issue in understanding the performance of pedotransfer functions (PTFs) is knowing the soil properties that contribute most to PTF errors. Classification trees provide a means for identifying these properties. The objective of this study was to use a classification tree to identify patterns in PTF residuals. The analysis was applied to PTFs developed by Vereecken and coworkers in 1989 to estimate water contents at −10 and at −1500 kPa. Errors below and above certain threshold values were defined as acceptable and unacceptable, respectively. The threshold acceptability values were assumed to be 0.04 and 0.01 cm3 cm−3 at −10 and −1500 kPa, respectively. The sensitivity of the trees to these values was studied by reducing them by 10%. Tentative predictors of the trees were sand, silt, and clay contents, bulk density (BD), soil organic C (OC) content, and horizon position (HP) in the soil profile (topsoil or subsoil). At −10 kPa, unacceptable data sets had very low clay contents or low BDs, given the poor representation of soil structure in the PTFs. At −1500 kPa, the unacceptable data sets had high clay and low OC contents with a HP of subsoil, or had high clay and high OC. Results were found to be moderately sensitive to small variations in the threshold. The least accurate estimates occurred for conditions in which the attributes used in the PTF were probably insufficient to unambiguously determine soil water retention data. Our study showed that classification trees can be helpful in identifying most optimal predictors for a PTF.