Introduction: Hepatocellular carcinoma (HCC) is a significant cause of mortality and morbidity in patients with cirrhosis. Using laboratory tests to identify patients at high risk for developing HCC may improve outcome and reduce the cost of screening in this patient population. Methods: In this retrospective study, we included all adult patients evaluated for liver transplantation between 1993 and 2012 at a single university-based transplant center. We used the hospital database and electronic medical records to obtain patients' demographics and laboratory data. ICD-9 code was used to determine patients who developed HCC. Results: A total of 3284 Patients were included in the study. Patients were predominantly white (86%), male (56%), with mixed etiology of cirrhosis (26% viral, 17% EtOH, 52% other), had a mean age of 54 years (SD 11.4), MELD of 10 (SD 5.1), albumin 3.7 (SD 0.7), creatinine 1.0 (SD 0.7), INR 1.3 (SD 0.3),bilirubin 1.9 (SD2.8) and platelet count of 149,000 (SD 94,000). After a follow up of 2.7 years (SD 2.7), 5% developed HCC, 24% died, and 10% underwent liver transplantation. In univariate analyses, the following parameters were predictive of HCC risk: age (HR 1.018, 95% CI 1.004-1.032, p 0.01), male gender (HR 3.268, 95% CI 2.265-4.715, p <0.0001), INR (HR1.896, 95% CI 1.418-2.534, p <0.0001), albumin (HR 0.453, 95% CI 0.367-0.561, p <0.001), platelet count (HR 0.991, 95% CI 0.989-0.994, p <0.0001), bilirubin (HR 1.062, 95% CI 1.010-1.117, p 0.02) and MELD (HR 1.060, 95% CI 1.030-1.091, p <0.0001). Creatinine was not predictive. In multivariate analysis, only age, male gender, platelet count, and albumin were predictive of HCC. Patients with platelet count <100,000 and albumin <3 had the highest annual actuarial risk for HCC of 6.2%. Conclusion: older males with low platelet count and albumin level are at higher risk for developing HCC. The interval of HCC screening for males with platelet count <100,000 and albumin < 3 g/dl may need to be shortened. Further prospective studies are warranted to determine the optimal screening interval.