AIM: To evaluate the addition of fasting glucose and lipids to a simple, validated risk prediction tool for gestational diabetes (GDM) applied in early pregnancy. METHODS: Women at risk of developing GDM on a validated risk prediction tool were recruited in early pregnancy into a large randomised controlled trial. Outcome measures included fasting biochemical markers (glucose, lipids) at 12-15 weeks gestation and GDM diagnosis (28 weeks gestation). Multivariable logistic regression was used to identify additional predictive biochemical variables for GDM, with corresponding receiver operator characteristic (ROC) curves generated. Unadjusted and adjusted models were derived for both the Australasian Diabetes in Pregnancy (ADIPS) and the International Association for Diabetes in Pregnancy Study Group (IADPSG) GDM diagnostic criteria. RESULTS: 51 (23%) Women were diagnosed with GDM based on ADIPS criteria, with 60 (30%) diagnosed based on IADPSG criteria. In all four regression models, fasting glucose was the strongest predictor for GDM development with an odds ratio range of 4.7-6.3 (ADIPS) and 8.8-10 (IADPSG). ROC curves revealed an area under the curve of 0.79 (95% CI: 0.72-0.86) for ADIPS criteria and 0.83 (95% CI: 0.77-0.90) for IADPSG criteria for adjusted models. CONCLUSIONS: In a two-step approach, when applied with a validated risk prediction tool, fasting glucose in early pregnancy was predictive of GDM and incrementally improved risk identification, presenting potential for an early pregnancy, GDM risk screening strategy for streamlining of pregnancy care and opportunity for preventive intervention.