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Accurate quantification of islet mass is critical for the preclinical evaluation and therapeutic application of stem cell-derived pancreatic islet organoids. Traditional methods, including Ricordi's islet equivalent (IEQ) approach and its equivalent circle diameter adaptations, often overestimate islet volume due to reliance on maximal diameters and discrete size bins. To address these limitations, we developed an automated image segmentation and three-dimensional modeling framework to quantify individual islet clusters from brightfield images. Clusters were fitted with ellipses and modeled as ellipsoids using rotation about either the minor or major axis, allowing IEQs to be calculated continuously relative to a reference 150 μm spherical islet. Major-axis (prolate) rotation provided the most conservative and physically plausible volume estimates, whereas minor-axis (oblate) rotation and diameter-based approaches systematically overestimated IEQs. Functional assessment with glucose-stimulated insulin secretion assays across multiple size categories demonstrated consistent insulin output for clusters below 250 μm, supporting the reproducibility of our 3D differentiation system. In vivo, streptozotocin-induced diabetic mice transplanted with islet doses based on major-axis modeling exhibited faster and more stable restoration of glycemia compared with groups receiving doses derived from overestimated approaches. These findings establish that major-axis ellipsoid modeling offers a mathematically consistent, conservative, and biologically relevant method for estimating IEQs, providing a practical framework to guide dosing in preclinical studies and supporting the translational development of stem cell-derived islet therapies.