As the global prevalence of chronic liver disease continues to rise, the need to determine which patients will develop end-stage liver disease and require liver transplantation is increasingly important. However, current prognostic models perform sub-optimally. We aim to determine microRNA profiles associated with clinical decompensation and mortality/transplantation within 1 year. We examined microRNA expression profiles in plasma samples from patients across the spectrum of cirrhosis (n = 154), acute liver failure (ALF) (n = 22), sepsis (n = 20) and healthy controls (HC) (n = 20). We demonstrated that a microRNA-based model (miR-24 and -27a) associated with systemic inflammation differentiated decompensated cirrhosis states from compensated cirrhosis and HC (AUC 0.77 (95% CI 0.69-0.85)). 6 patients within the compensated cirrhosis group decompensated the subsequent year and their exclusion improved model performance (AUC 0.81 (95% CI 0.71-0.89)). miR-191 (associated with liver injury) predicted risk of mortality across the cohort when acutely decompensated and acute-on-chronic-liver failure patients were included. When they were excluded miR-24 (associated with systemic inflammation) predicted risk of mortality. Our findings demonstrate that microRNA associated with systemic inflammation and liver injury predict adverse outcomes in cirrhosis. miR-24 and -191 require further investigation as prognostic biomarkers and therapeutic targets for patients with liver disease.