Fibromyalgia (FM) patients show characteristically enhanced unpleasantness to painful and non-painful sensations accompanied by altered neural responses. The diagnostic potential of such neural alterations, including their sensitivity and specificity to FM (vs. healthy controls) is unknown. We identify a brain signature that characterizes FM central pathophysiology at the neural systems level. We included 37 FM patients and 35 matched healthy controls, and analyzed fMRI responses to (i) painful pressure and (ii) non-painful multisensory (visual-auditory-tactile) stimulation. We used machine-learning techniques to identify a brain-based FM signature. When exposed to the same painful stimuli, FM patients showed greater Neurologic Pain Signature (NPS, Wager 2013) responses. In addition, a new pain-related classifier (‘FM-pain’) revealed augmented responses in sensory integration (insula/operculum) and self-referential (e.g., medial prefrontal) regions in FM, and reduced responses in the lateral frontal cortex. A ‘Multisensory’ classifier trained on non-painful sensory stimulation revealed augmented responses in insula/operculum, posterior cingulate, and medial prefrontal regions, and reduced responses in primary/secondary sensory cortices, basal ganglia and cerebellum. Combined activity in the NPS, FM-pain, and Multisensory patterns classified patients vs. controls with 92% sensitivity and 94% specificity in out-of-sample individuals. Enhanced NPS responses partly mediated mechanical hypersensitivity, and correlated with depression and disability(puncorrected<0.05); FM-pain and Multisensory responses correlated with clinical pain(puncorrected<0.05). The study provides initial characterization of individual FM-patients based on pathophysiological, symptom-related brain features. If replicated, these brain features may constitute objective neural targets for therapeutic interventions. The results establish a framework for assessing therapeutic mechanisms and predicting treatment response at the individual level.