The size composition of human islet preparations has been attributed to functional potency, islet survival and transplantation outcomes. In the early post-transplantation phase islets are supplied with oxygen by diffusion only and are at risk of critical hypoxia. The high rate of early islet graft dysfunction is in part attributed to this condition. It has been presumed that islets with smaller diameter, and therefore smaller diffusion distance, are superior to large islets regarding early survival rate and graft function. In this study we aimed to evaluate Complex Object Parametric Analysis and Sorting (COPAS) as a device for automated sorting of human islets. The use of COPAS was validated for accuracy and sensitivity using polystyrene beads of known diameters. Based on time of flight relative to particle isolated islets were then automatically sorted and analyzed for viability and function using handpicked islets as control. Our results suggest that COPAS enables the automated and accurate sorting of islets with no negative impact on their integrity and viability. Thus, COPAS is an adequate tool for size-specific analysis of pancreatic islets and may be considered as part of a platform for automated high-throughput screening of pancreatic islets.