Abstract: Water scarcity is a major threat to crop production and quality. Improving drought tolerance through variety selection requires a deeper understanding of plant ecophysiological responses, but large-scale phenotyping remains a bottleneck. This study assessed the potential of high-throughput tools (spectroscopy and poro-fluorometry) to predict leaf morphological and ecophysiological traits in a grapevine diversity panel grown in pots under well-watered outdoor conditions and under three contrasting soil water treatments in a greenhouse. We found a certain complementarity between measuring devices. Spectrometers could accurately predict leaf mass per area, water content, and water quantity (R2 > 0.58), while the poro-fluorometer was efficient for predicting net CO2 assimilation (R2 > 0.72), regardless of the water treatment. The prediction of leaf mass per area using spectrometers appeared to be quite robust across both outdoor and greenhouse experiments, while the prediction of water use efficiency was dependent on the water treatment, with much better predictions under moderate (R2 > 0.73) than severe water deficit. Calibrated models were then applied to the full diversity panel using only high-throughput measurements to estimate trait values and their broad-sense heritability. Leaf mass per area, also measured directly, showed similar heritability whether based on observed or predicted data. Heritability estimates for predicted traits reached up to 0.5. Overall, our findings support the use of spectroscopy and poro-fluorometry as reliable, nondestructive tools for high-throughput phenotyping, enabling genetic studies on drought-related traits in grapevine. Plain Language Summary: Drought is a major challenge for crop production. To breed grapevines that can better tolerate dry conditions, it is crucial to evaluate how plants respond to water stress using quick phenotyping tools. In this study, we tested two fast, nondestructive tools, near-infrared spectroscopy and poro-fluorometry, on grapevines grown with different water levels. Spectroscopy was accurate for evaluating leaf thickness and water content, while poro-fluorometry was better at predicting photosynthesis. These tools were effective even across different growing environments. The results demonstrate that these methods can aid in estimating genetic variability in drought-related traits, facilitating the selection and improvement of drought-tolerant grapevines.