Reduced nicotinamide adenine dinucleotide (NADH) and oxidized flavin adenine dinucleotide (FAD) are coenzymes of cellular metabolism reactions, and their endogenous fluorescent signals are used to evaluate cell redox state and detect changes in cellular metabolism. Different cellular metabolic states can alter NADH and FAD fluorescence features. Here, a model is developed to determine T cell metabolic pathway utilization from autofluorescence lifetime imaging features. The model is trained and tested using cellular features extracted from NADH and FAD fluorescence lifetime images of activated and quiescent T cells with chemical inhibition of glycolysis, oxidative phosphorylation, glutaminolysis, and fatty acid synthesis. Feature analysis revealed the optical redox ratio (FAD intensity/ (NADH intensity + FAD intensity), the fluorescence lifetime redox ratio (fraction of bound NADH/fraction of bound FAD), and the fluorescence lifetime of free NADH are the highest weighed features for classification of T cells dependent on glycolysis versus oxidative metabolism. High classification accuracy is achieved for discrimination between quiescent and activated T cells, and modest classification accuracy is achieved for classification of T cells into metabolic subgroups. Autofluorescence features vary between cytoplasm and mitochondria and analyzing this difference can provide additional metabolic information. Altogether, these results demonstrate the potential for autofluorescence lifetime imaging features to classify T cell function and metabolic state.