Metabolic Syndrome is an entity characterized by central obesity, fasting raised glucose, lipid disorders, raised blood pressure and insulin resistance. All these features coexist together and lead to diabetes mellitus and cardiovascular complications. Rapid urbanization, modernization and growth in population in developing countries have led to an increase in non-communicable diseases including Metabolic Syndrome. Over the last 20 years, there has been prominent increase in subjects with Metabolic Syndrome. High prevalence is a worldwide trend and available data indicates that 28% to 30% of adult population in most countries can be labeled as having Metabolic Syndrome. The prevalence in Pakistan is between 18% and 46%. This study was conducted on 300 subjects (150 control and 150 having Metabolic Syndrome according to International Diabetes Federation criteria) including males and females aged from 20 to 40 years to detect Metabolic Syndrome with different easily available routine markers like anthropometric (body mass index, hip circumference, waist hip ratio, body fat percentage, visceral fat level and neck circumference), biochemical (serum uric acid, serum insulin, total cholesterol, low density lipoprotein cholesterol and glycated hemoglobin), inflammatory and adipokine including white blood cell count,high sensitivity C reactive protein and serum chemerin. The objective of current study was to find out significant marker for prediction of Metabolic Syndrome. The data were analyzed on SPSS version 22.0. The results of this study showed significantly increased levels of body mass index, waist circumference, hip circumference, waist hip ratio, neck circumference, systolic blood pressure, diastolic blood pressure, body fat percentage and visceral fat level in subjects with Metabolic Syndrome when compared to controls, both in males and females with p value < 0.0001. Biochemical parameters like total cholesterol, low density lipoprotein cholesterol, triglycerides, serum uric acid, glycated hemoglobin, fasting blood glucose, serum insulin and homeostasis model assessment Insulin resistance were also found significantly increased in subjects of Metabolic Syndrome when compared with controls while high density lipoprotein cholesterol was found significantly decreased in Metabolic Syndrome subjects compared to controls. Adipokine and inflammatory parameters like chemerin, white blood cell count and high sensitivity C reactive protein were significantly increased in Metabolic Syndrome subject when compared with controls. Anthropometric measurements like body mass index, hip circumference, waist hip ratio and visceral fat level were highly correlated with components of Metabolic Syndrome. Furthermore, among Inflammatory, adipokine and Biochemical Parameters, serum uric acid, chemerin, high sensitivity C reactive protein and white blood cell counts were highly correlated with component of Metabolic Syndrome. When correlation analysis was further carried on gender basis, it was found that body mass index, hip circumference and visceral fat level among males were more correlated with components of Metabolic Syndrome as compared to females, whereas, waist hip ratio among females was more correlated with Metabolic Syndrome. Moreover, serum uric acid, high sensitivity C reactive protein and white blood cell count were more correlated with Metabolic Syndrome among males as compared to female. However, chemerin was highly correlated among both male and female. Among anthropometric parameters body mass index, neck circumference and visceral fat level were most prominent risks for Metabolic Syndrome. And among inflammatory, adipokine and biochemical parameters except white blood cell count all parameter were good risks for Metabolic Syndrome. When logistic regression analysis was applied gender-wise it was observed that odds ratio of female body mass index (5.037, p<0.0001) was higher than body mass index (4.59, p<0.0001) of male participants. Whereas, neck circumference and visceral fat level odds ratio were higher for males as compared to females. Moreover, for serum uric acid and serum insulin odds ratio were higher among female and for chemerin and high sensitivity C reactive protein odds ratio among males were higher. Among anthropometric measurements on Receiver Operating Characteristic curve analysis body mass index (Area Under Curve, 98.90%) and visceral fat level (Area Under Curve, 99.70%) were shown as best predictors and among inflammatory, adipokine and biochemical markers chemerin (Area Under Curve, 99.98%), serum insulin (Area Under Curve, 99.20%) and high sensitivity C reactive protein (Area Under Curve, 98.50%) were most highlighted markers. Moreover, gender-wise it was identified that there was not much difference among sensitivity, specificity and cut off values of body mass index, hip circumference and visceral fat level, however, cut off value for body fat percentage for females were higher than males and cut off value of neck circumference for male was higher than female. Moreover, cut off values of serum uric acid, chemerin and serum insulin among female were higher than male. After correlation, regression and receiver operating characteristic curve analysis it was concluded that body mass index (cut-off 24.3 kg/m2 in males and 24.01 kg/m2 in females) and visceral fat level (9.5 in males and 8.5 in females) are the most prominent markers while chemerin ( cut-off 40.05 ng/dl in males and44.3 ng/dl in females) and high sensitivity C reactive protein (cut-off 4.45 mg/L in males and 3.5 mg/L in females) were the most prominent predictors for development of Metabolic Syndrome in both sexes. Further Research is needed with inclusion of more and newly introduced anthropometric, adipokine and inflammatory markers on large scale to cope with rising number of Metabolic Syndrome subjects to reduce the cost of health expenses.