AbstractRainfall interception (RI) by forest canopies is an important process in hydrological cycling in forest ecosystems. However, accurately predicting RI is a challenging topic. In this study, a dimensionless descriptor, canopy interception index (CII), for predicting RI was defined. The terrestrial laser scanning was used to estimate CII in four temperate forest types, including Korean pine (Pinus koraiensis) plantation forest (KPF) stands, larch (Larix spp.) plantation forest (LPF) stands, mixed broadleaved forest (MBF) stands and Mongolian oak (Quercus mongolica) forest (MOF) stands. Using the measured RI values over the rainy seasons in 2017 and 2018, CII's performance for predicting RI was tested and also compared with several other indices (LAI: leaf area index, PAI: plant area index and ACH: average canopy height). The results indicated that CII was significantly and strongly related with RI for the four forest types together (R2 = 0.79), as well as for an individual forest type (R2 = 0.55–0.63). More importantly, its performance was better than those from LAI (R2 = 0.33–0.43), PAI (R2 = 0.40–0.53) and ACH (R2 = 0.35). All those results demonstrated that CII was an efficient index for accurately predicting RI. The potential applications of CII were also discussed.