Analyzing metabolism of peripheral blood mononuclear cells (PBMCs) provides key opportunities to study the pathophysiology of several diseases, such as type 2 diabetes, obesity and cancer. Extracellular flux (XF) assays provide dynamic metabolic analysis of living cells that can capture ex vivo cellular metabolic responses to biological stressors. To obtain reliable data from PBMCs from individuals, novel methods are needed that allow for standardization and take into account the non-adherent and highly dynamic nature of PBMCs. We developed a novel method for extracellular flux analysis of PBMCs, where we combined brightfield imaging with metabolic flux analysis and data integration in R. Multiple buffy coat donors were used to demonstrate assay linearity with low levels of variation. Our method allowed for accurate and precise estimation of XF assay parameters by reducing the standard score and standard score interquartile range of PBMC basal oxygen consumption rate and glycolytic rate. We applied our method to freshly isolated PBMCs from sixteen healthy subjects and demonstrated that our method reduced the coefficient of variation in group mean basal oxygen consumption rate and basal glycolytic rate, thereby decreasing the variation between PBMC donors. Our novel brightfield image procedure is a robust, sensitive and practical normalization method to reliably measure, compare and extrapolate XF assay data using PBMCs, thereby increasing the relevance for PBMCs as marker tissue in future clinical and biological studies, and enabling the use of primary blood cells instead of immortalized cell lines for immunometabolic experiments.