Goals: To develop a noninvasive algorithm for diagnosis of liver steatosis and to compare its diagnostic value with available predictive models. Background: Liver steatosis represents the most frequent liver disease worldwide. Study: This cross-sectional study analyzed data from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). Patients were randomly divided into training (n=6571) and validation (n=3286) cohort. Abdominal ultrasound (US), used to grade steatosis, and overnight fasting blood tests were performed at the same day. Fatty Liver Index (FLI), Hepatic Steatosis Index, and Nonalcoholic Fatty Liver Disease-Liver Fat Score were calculated. A backward stepwise multivariate logistic regression analysis was used to develop the new predictive model, Steato-ELSA. Results: In total, 9857 subjects [58% female, age= 51 (interquartile range, 45 to 58) years, body mass index=26.4 (23.9 to 29.6) Kg/m2 were included. Body mass index, waist circumference, homeostasis model of assessment of insulin resistance, transaminases, and triglycerides were independently associated with steatosis in the multivariate model (Hosmer-Lemeshow P= 0.279). In the validation cohort, the area under the receiver-operator characteristics (95% confidence interval) for prediction of mild and moderate steatosis were: (i) 0.768 (0.751-0.784) and 0.829 (0.810-0.848) for Steato-ELSA; (ii) 0.762 (0.745-0.779) and 0.819 (0.799-0.838) for Fatty Liver Index; (iii) 0.743 (0.727-0.761) and 0.800 (0.779-0.822) for Hepatic Steatosis Index; and (iv) 0.719 (0.701-0.737) and 0.769 (0.747-0.791) for Nonalcoholic Fatty Liver Disease-Liver Fat Score. Steato-ELSA performed significantly better than other models and yielded sensitivity (Se)/specificity (Sp) (95% confidence interval): (i) for mild steatosis (score ≥ 0.386): Se = 65.6% (63.0-68.3) and Sp = 73.7% (71.8-75.6); (ii) for moderate steatosis (score ≥ 0.403): Se = 83.5% (80.0-86.9) and Sp = 68.7% (67.0-70.4). Conclusions: Steato-ELSA is an accurate and inexpensive tool that uses simple parameters to identify individuals at high risk of liver steatosis.