Author Summary We quantified the reliability of fMRI functional connectivity in a large sample of healthy participants ( N = 833) scanned over two consecutive days. We also assessed the consequences on reliability of atlas choice, global signal regression and thresholding. Only a small portion of the functional connectome has good (6–8%) to excellent (0.08–0.14%) reliability. Connectivity between prefrontal, parietal and temporal areas is especially reliable and average connectivity within known networks has good reliability. While unreliable edges are generally weak, reliable edges are not necessarily strong. Reliability of edges varies between atlases. Global signal regression decreases reliability for networks and most edges (but increases it for some). Thresholding based on connection strength reduces reliability. Focusing on reliable portions of the connectome could help investigate individual differences using functional neuroimaging. Abstract Countless studies have advanced our understanding of the human brain and its organization by using functional magnetic resonance imaging (fMRI) to derive network representations of human brain function. However, we do not know to what extent these “functional connectomes” are reliable over time. In a large public sample of healthy participants ( N = 833) scanned on two consecutive days, we assessed the test-retest reliability of fMRI functional connectivity and the consequences on reliability of three common sources of variation in analysis workflows: atlas choice, global signal regression, and thresholding. By adopting the intraclass correlation coefficient as a metric, we demonstrate that only a small portion of the functional connectome is characterized by good (6–8%) to excellent (0.08–0.14%) reliability. Connectivity between prefrontal, parietal, and temporal areas is especially reliable, but also average connectivity within known networks has good reliability. In general, while unreliable edges are weak, reliable edges are not necessarily strong. Methodologically, reliability of edges varies between atlases, global signal regression decreases reliability for networks and most edges (but increases it for some), and thresholding based on connection strength reduces reliability. Focusing on the reliable portion of the connectome could help quantify brain trait-like features and investigate individual differences using functional neuroimaging.