Assessing residual consciousness and cognitive abilities in unresponsive patients is a major clinical concern and a challenge for cognitive neuroscience. Although neuroimaging studies have demonstrated a potential for informing diagnosis and prognosis in unresponsive patients, these methods involve sophisticated brain imaging technologies, which limit their clinical application. In this study, we adopted a new language paradigm that elicited rhythmic brain responses tracking the single-word, phrase and sentence rhythms in speech, to examine whether bedside electroencephalography (EEG) recordings can help inform diagnosis and prognosis. EEG-derived neural signals, including both speech-tracking responses and temporal dynamics of global brain states, were associated with behavioral diagnosis of consciousness. Crucially, multiple EEG measures in the language paradigm were robust to predict future outcomes in individual patients. Thus, EEG-based language assessment provides a new and reliable approach to objectively characterize and predict states of consciousness and to longitudinally track individual patients' language processing abilities at the bedside.