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Despite all efforts, obesity remains a major health concern worldwide, with continuously increasing rates, affecting approx. 14% of the total world population, being as high as 43% in some countries. As obesity is related to numerous comorbidities, including type 2 diabetes, cardiovascular diseases, and some types of cancer, the consequences for the individual and society at large are drastic. Therefore, it is crucial to understand and predict who is at risk of developing obesity in order to implement early prevention strategies. Many individual risk factors have been emphasized. However, as obesity is a rather multifactorial complication, single markers/biomarkers have thus far not allowed for an efficient prediction of obesity. In addition to less modifiable parameters, such as environment and socio-demographics, studies have revealed that obesity is related to several interacting aspects, including host factors such as genetics/epigenetics or gut microbiota, and more readily modifiable factors, including nutrition and physical activity, as well as sleep patterns and psychological well-being. It is likely that combining markers from across different domains, that is, multimodal markers, allows for better predictability for the risk of developing obesity. However, it must be considered that not all markers are fully predictive; many are rather reactive or even both. In this review and position paper, we emphasize the state-of-the-art regarding (bio)markers that have successfully been employed for predicting obesity risk. An emphasis will rest on novel, emerging biomarkers, and the need for a more integrative, multimodal assessment of obesity risk for a combined assessment aimed at improving risk prediction.