Fat-to-muscle ratio has been proposed as an alternative approach for assessing body fat. The objective of this study was to explore fat-to-muscle ratio thresholds in metabolic syndrome (MetS) diagnosis; it was hypothesised that the fat-to-muscle ratio is a good predictive indicator of MetS in a large population of young Colombian adults. For this purpose, a cross-sectional study was conducted on 1416 subjects (66.6% female), aged from 18.1 to 25.1. As part of the study, measurements of the subjects’ anthropometric indicators, serum lipid indices, blood pressure, and fasting plasma glucose were taken. Body composition was measured through bioelectrical impedance analysis (BIA). A new variable (ratio of fat mass to muscle mass, in kg) was calculated. Following the International Diabetes Federation (IDF) definition, MetS includes three or more metabolic abnormalities. Receiver operating characteristic (ROC) curves and logistic regression determined the discriminatory ability of the fat-to-muscle ratio to predict MetS. According to the IDF, the best fat-to-muscle ratio cut-off point for detecting MetS in men was 0.225 kg, with an area under the curve (AUC) of 0.83, sensitivity of 80%, and specificity of 70%. For women, the fat-to-muscle ratio cut-off point was 0.495 kg, the AUC was 0.88, and the sensitivity and specificity were 82% and 80%, respectively. In conclusion, our results showed that the fat-to-muscle ratio cut-off points from ROC analyses demonstrate good discriminatory power for detecting MetS in young Colombian adults.