Summary Metabolic syndrome is a complex of interrelated health conditions that pose a significant risk of developing cardiovascular disease, stroke, and type 2 diabetes. Resistance to insulin, genetic predisposition, high blood pressure, inflammation, and excess abdominal fat are the main stimuli of this syndrome. Metabolic syndrome is becoming more widespread due to fast and unplanned urbanization causing changes in lifestyle, such as poor dietary habits and sedentary behavior, that decrease the metabolic rate in the human body. A developing South Asian country like Bangladesh is most vulnerable to components of metabolic syndrome such as obesity, hypertension and diabetes. Consequently, it has become one of the major public health concerns. Prediction of disease status is a key component of community and health service policymaking. A nationally representative cross-sectional survey, the Bangladesh Demographic and Health Survey (BDHS), is used to find statistically significant variables for metabolic syndrome. BDHS datasets do not contain any direct data regarding metabolic syndrome. A binary variable is generated by utilizing the available data on blood pressure, blood glucose level, and body mass index (BMI). Overall, 34.33% of the population has metabolic syndrome. Primarily, bivariate analysis is performed using chi-square testing to find variables that are correlated with metabolic syndrome. Results of binary logistic analysis are presented in terms of coefficients and odds ratios (OR) with 95% confidence intervals (CI). Age, gender, education, division (province), occupation type, and wealth index are found to be important covariates for the syndrome. Age especially is seen as one of the most influential factors, since the prevalence of metabolic syndrome is only 12.17% for the age group younger than 18 years, while for the group older than 65 years it is 62.18%. Residents of Barishal have the highest rate of metabolic syndrome (38.58%). The rate in the country’s capital Dhaka is 34.48%. Individuals whose employment primarily involves manual labor are 11.1% less likely to suffer from metabolic syndrome than those doing non-manual work.