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BACKGROUND Falls are a devastating complication of cirrhosis. The risk of falls in contemporary patients without HE is unclear. Further, bedside tools for predicting falls are lacking METHODS: We prospectively enrolled 299 subjects with currently compensated Child A-B (70% Child A) cirrhosis and portal hypertension without prior HE from 7/2016-8/2018. We followed patients for a median of 1003 days (IQR640-1102) for incident falls accounting for the competing risk of death or transplantation. Candidate baseline fall predictors included patient reported outcomes (e.g. SF-8), physical function (e.g. chair-stands), blood tests (e.g. MELD-Na and its components), and cognitive function (using Inhibitory Control Testing). We internally validated a predictive model for falls and evaluated the association between incident falls and mortality. RESULTS During follow-up, 141(47%) patients experienced falls, 38(13%) with injuries, 49(16%) died, and 13(4%) underwent transplants. Median time to a fall was 279(98-595) days. The overall probability of falls was 28.8% and 50.2% at years 1 and 3; the probability of injurious falls was 9.1% and 16.5%. We derived a predictive model for falls. The FallSSS score (prior falls, chair-stands, sodium, and SF-8) had an AUROC for injurious falls at 6- and 12-months of 0.79 and 0.81 while MELD-Na's AUROC was 0.57 for both. Adjusting for baseline Child class, MELD-Na, albumin level, disability status, and comorbidities, both incident falls - sHR 2.76 95%CI(1.46-5.24) - and HE - sHR 4.25 95%CH(2.15-8.41) - were strongly and independently associated with mortality. CONCLUSION Our prospective study of patients with cirrhosis without a baseline history of HE demonstrates that falls are common, morbid, and predictable. These data highlight both the value of expanding screening to patients with cirrhosis and the potential for benefit in studies of interventions to address fall-risk in this vulnerable population. LAY SUMMARY Falls are a devastating complication of cirrhosis. Bedside tools for predicting falls are lacking. We found that falls were very common and often associated with serious injuries. Falls were also associated with an increased risk of death. Falls could be predicted with an algorithm called FallSSS - based on prior history of falls, blood sodium level, number of chair-stands performed in 30 seconds, and quality of life.