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Macropore flow is a gravity-driven phenomenon that exhibits high contamination risk for surface and shallow groundwater. In order to address the necessity of having reliable and tangible indicators of macropore flow incidence, this research is an extensive data exploration that uncovers potential regional macropore flow incidence indicators that are synthesized as hypotheses for future research. CART-based regression trees are used to uncover significant relationships among soil physical properties, management regimes, field saturated hydraulic conductivity, saturated soil air-entry tensions and earthworm biomass. All of the modeling is based on field-measured data. Prediction scenarios are established in order to develop potential regional indicators of field saturated hydraulic conductivity (Kfs), soil saturated air-entry tension (AEV), and earthworm biomass. The magnitude, range, and pattern of variability of soil water infiltrations are controlled primarily by the well-developed and stable soil structure at the field scale, rather than by texture, organic carbon or surface topography, as classical pedotransfer functions suggest. Tillage is influential for the estimation of all targeted variables. Conventional tillage is associated with rapid shallow infiltration rates and lower air entry tensions both in the cultivation layer and below. Absence of tillage is found to be beneficial for earthworm communities as sampled biomass is greater on no-till field sites. The strong correlations between Kfs and AEV demonstrate good prediction potential but because of their intrinsic spatial and temporal variability, their utility as regional macropore flow indicators is questionable.