Leaf anatomical parameters such as leaf mass per area (LMA) and biochemical composition can be used as indicators of leaf photosynthetic capacity. The aims of this study are to evaluate the potential of reflectance spectroscopy of fresh leaves for assessing and predicting various parameters, anatomical (LMA and tissue thickness) and biochemical (nitrogen concentration). This paper describes results obtained with fresh leaves of holm oak (Quercus ilex), an evergreen oak that is widely distributed from mesic to xeric habitats in the Mediterranean. Fresh leaves (560) were collected over 3 yr at six different sites, from the top to the bottom of the canopy. The reflectance of each leaf was obtained within 1 h of sampling with an NIRSystems 6500 spectrophotometer over the range 400–2500 nm. LMA was determined for all samples; biochemical and anatomical measurements were conducted over representative subsample populations of 92 and 87 leaves, respectively. Stepwise regression calibrations and partial least squares (PLS) calibrations were developed and compared with different spectral regions and mathematical treatments. Calibration equations had high coefficients of determination (r2 ranging from 0.94 for nitrogen to 0.98 for LMA and tissue thickness). The PLS regressions gave better results than stepwise regressions for all parameters studied. Compared with regressions calculated on raw spectral data, calculations on second derivatives of spectra improved results in all cases. The use of scatter corrections also improved results. These results show that visible and near-infra red reflectance can be used for accurately predicting anatomical parameters and the nitrogen concentration of fresh holm oak leaves. The results support the suggestion that high spectral resolution imaging spectrometry can be a useful tool for assessing functional processes in forest ecosystems.