Resting-state fMRI (RS-fMRI) measures spontaneous low-frequency fluctuations in the BOLD signal to investigate the functional architecture of the brain. Various resting-state networks (RSNs) have been identified, including the default mode network (DMN), somatosensory network, visual network, and attentional networks. RS-fMRI analysis methods include seed-based approaches, independent component analysis (ICA), graph methods, clustering algorithms, neural networks, and pattern classifiers. Clinical applications of RS-fMRI are still in their early stages but show promise in presurgical planning for brain tumors and epilepsy, as well as in diagnosing and prognosticating neurological and psychiatric diseases. RS-fMRI is particularly useful for patients who cannot cooperate with task-based paradigms, such as young children, patients with altered mental status, or those who are sedated or paretic. Future research will focus on comparing different analysis methods and their efficacy in detecting various disease states, both in groups and individual subjects.Resting-state fMRI (RS-fMRI) measures spontaneous low-frequency fluctuations in the BOLD signal to investigate the functional architecture of the brain. Various resting-state networks (RSNs) have been identified, including the default mode network (DMN), somatosensory network, visual network, and attentional networks. RS-fMRI analysis methods include seed-based approaches, independent component analysis (ICA), graph methods, clustering algorithms, neural networks, and pattern classifiers. Clinical applications of RS-fMRI are still in their early stages but show promise in presurgical planning for brain tumors and epilepsy, as well as in diagnosing and prognosticating neurological and psychiatric diseases. RS-fMRI is particularly useful for patients who cannot cooperate with task-based paradigms, such as young children, patients with altered mental status, or those who are sedated or paretic. Future research will focus on comparing different analysis methods and their efficacy in detecting various disease states, both in groups and individual subjects.