Background The prevalence of the metabolic syndrome (MetS) is increasing worldwide. Early detection of the MetS by valid and available indicators can help prevent, control and reduce its complications. This study aims to identify of most important anthropometric, biochemical and nutritional indices for predicting MetS. Methods This study conducted on 9,602 participants from baseline data of the Ravansar Non-Communicable Disease (RaNCD) cohort study including of adults aged 35–65 years. The reference model for MetS was considered according to International Diabetes Federation (IDF) criteria. We used a wrapper algorithm and area under ROC curve (AUC) for selection and assessing most important predictors of MetS. Results The importance value (IV) for components of the models for prediction of MetS was confirmed, before implementing the models. Identified model with components of age, waist circumference (WC), body mass index (BMI), fasting blood sugar (FBS), systolic-diastolic blood pressure (SBP-DBP), triglyceride (TG), hip circumference (HC) and AUC of 0.893 (95% CI: 0.884–0.902) for men and 0.867 (95% CI: 0.853–0.881) for women was a strongest model for predictive of MetS risk. The AUC (95% CI) for non-invasive model was 0.756 (0.746–0.766) in total population has a good predictive power for MetS risk with components of age, WC, BMI, SBP, DBP. Conclusion This study demonstrated that in addition to aggressive models, models non-invasive (anthropometric indices, blood pressure and energy intake) can be also a good and convenience screening tool to predict the MetS. The models, in addition to the application of clinical diagnosis, can be widely used in researches on large populations.