The discussion about the diagnosis and treatment of type 2 diabetes - and, more generally, dysglycaemia - should be framed in terms of a continuum of risk. A variety of tools have been developed to identify individuals with an increased risk of developing type 2 diabetes and to quantify the probability of type 2 diabetes either cross-sectionally or prospectively. Such scores are based on traditional risk factors for diabetes, such as age, body mass index (BMI), and family history, while others also evaluate metabolic risk factors such as lipid levels. The performance of a diabetes risk-prediction tool is generally assessed by measuring its accuracy, availability, practicability, and costs. This review discusses the validity and use of today's available major risk-prediction tools for clinical practice, and assesses the scope and cost-effectiveness of available tools. Among these prediction tools, American Diabetes Association (ADA) Risk Tools, Finnish Diabetes Risk Score (FINDRISC), National Health and Nutrition Examination Survey (NHANES) Risk Score, and Study to Prevent Non-Insulin Dependents Diabetes Mellitus (STOP-NIDDM) Risk Score were of our concern. We conclude that the FINDRISC tool is currently the best available tool for use in clinical practice in Caucasian populations, but modifications may be required if applied to other ethnic groups.