Resting state functional connectivity (fcMRI) is a promising tool for clinical applications, offering insights into brain function through spontaneous BOLD signal fluctuations. This technique identifies correlations between brain regions, revealing functional connectivity patterns that can help understand neurological and psychiatric diseases. Unlike task-based fMRI, fcMRI does not require active tasks, making it suitable for patients who cannot perform tasks due to cognitive or physical impairments. It also provides better signal-to-noise ratios, as spontaneous activity is analyzed rather than discarded as noise. This makes fcMRI more effective in detecting subtle brain abnormalities. fcMRI has been used to study various neurological and psychiatric conditions, including Alzheimer's disease, schizophrenia, and depression. It has shown potential in identifying biomarkers for diagnosis and prognosis, as well as in monitoring treatment effects. For example, fcMRI has been used to assess the impact of drug treatment on depression and to evaluate recovery in stroke patients. It is also valuable in pre-operative brain mapping, helping surgeons avoid critical brain areas during surgery. Despite its promise, challenges remain in translating fcMRI into clinical practice. These include ensuring consistency across studies, addressing confounding factors, and improving the reproducibility of findings. Guidelines for conducting fcMRI studies in clinical populations emphasize the importance of a priori hypotheses, rigorous statistical corrections, and movement and preprocessing analyses. Collaboration and data sharing between research groups are essential for advancing the field and improving clinical applicability. Technological advancements, such as improved signal-to-noise ratios and multimodal investigations, are also crucial for enhancing the clinical utility of fcMRI. These developments, along with the creation of online databases for resting state fcMRI data, facilitate research and collaboration, accelerating the translation of findings into clinical practice. Overall, fcMRI holds significant potential for improving the diagnosis, prognosis, and treatment of brain disorders.Resting state functional connectivity (fcMRI) is a promising tool for clinical applications, offering insights into brain function through spontaneous BOLD signal fluctuations. This technique identifies correlations between brain regions, revealing functional connectivity patterns that can help understand neurological and psychiatric diseases. Unlike task-based fMRI, fcMRI does not require active tasks, making it suitable for patients who cannot perform tasks due to cognitive or physical impairments. It also provides better signal-to-noise ratios, as spontaneous activity is analyzed rather than discarded as noise. This makes fcMRI more effective in detecting subtle brain abnormalities. fcMRI has been used to study various neurological and psychiatric conditions, including Alzheimer's disease, schizophrenia, and depression. It has shown potential in identifying biomarkers for diagnosis and prognosis, as well as in monitoring treatment effects. For example, fcMRI has been used to assess the impact of drug treatment on depression and to evaluate recovery in stroke patients. It is also valuable in pre-operative brain mapping, helping surgeons avoid critical brain areas during surgery. Despite its promise, challenges remain in translating fcMRI into clinical practice. These include ensuring consistency across studies, addressing confounding factors, and improving the reproducibility of findings. Guidelines for conducting fcMRI studies in clinical populations emphasize the importance of a priori hypotheses, rigorous statistical corrections, and movement and preprocessing analyses. Collaboration and data sharing between research groups are essential for advancing the field and improving clinical applicability. Technological advancements, such as improved signal-to-noise ratios and multimodal investigations, are also crucial for enhancing the clinical utility of fcMRI. These developments, along with the creation of online databases for resting state fcMRI data, facilitate research and collaboration, accelerating the translation of findings into clinical practice. Overall, fcMRI holds significant potential for improving the diagnosis, prognosis, and treatment of brain disorders.