We are proposing a software, based on machine learning, which analyzes the data gathered in a task-based functional magnetic resonance imaging (fMRI) at early stages of MS and in Relapsing-Remitting MS (RRMS) suffers. MS causes disruptions in the brain network connectivity that can be determined using network analysis. Our proposed solution examines the changes in brain connectivity topologies induced by a specific cognitive task performance requiring attention, working memory, and information processing speed. As a result, cognitive impairment can be detected and treated at the very early stages of MS.