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Leaf chlorophyll content provides valuable information about the physiological status of plants, and there is a need for accurate, efficient, practical methodologies to estimate this biophysical parameter. Reflectance measurement is a means of quickly and nondestructively assessing, in situ, the chlorophyll content in leaves. The objective of this study was to develop a precise, efficient, nondestructive technique to estimate leaf total chlorophyll (Chl) content in grapes. A relationship was established between Chl content and the red-edge chlorophyll index, based on reflectances in the red-edge (710–720 nm) and near-infrared (755–765 nm) spectral ranges, and the algorithm for Chl retrieval was calibrated. The accuracy of Chl prediction using an independent data set, containing sampled leaves from three field-grown grape cultivars (Edelweiss, Saint Croix, and DeChaunac), was evaluated with no re-parameterization (adjustment of the coefficients) after initial calibration. Although Chl in the validation data set was widely variable, from 3 to 506 mg m-2, the calibrated algorithm was capable of accurately predicting grape leaf Chl with RMSE <30 mg m-2. Such an approach has potential for developing simple hand-held field instrumentation for accurate nondestructive Chl estimation and in analyzing digital airborne or satellite imagery to assist in vineyard management decision making.