Schizophrenia (SZ) is a complex neuropsychiatric disorder characterized by disrupted integration among distributed brain areas. Currently, there are no objective diagnostic tests for schizophrenia. The evaluation of brain network entropy can provide insights into understanding pathological connectomic anomalies in schizophrenia patients, and together with other cross-sectional data potentially suggest biomarkers for diagnosing this complex disease. Our study analyzed resting-state functional magnetic resonance imaging (fMRI) data from 314 subjects, including 153 with schizophrenia patients and 163 age-and gender-matched healthy controls. We focused on 47 functionally relevant intrinsic connectivity brain networks obtained by group independent component analysis (GICA) in a previous study. We evaluated static and dynamic connectivity entropies and found 22 intrinsic connectivity networks with significant differences in heterogeneity of connectivity levels across available networks between SZ patients and healthy controls. These networks are associated with subcortical (SC), auditory (AUD), visual (VIS), somatomotor (SM), cognitive control (CC), and cerebellar (CB) functional brain domains.