Despite high cure rates 25% of children with acute lymphoblastic leukaemia (ALL) relapse and have dismal outcome. Crucially, many are currently stratified as standard risk (SR) and additional markers to improve patient stratification are required. Here we have used diagnostic bone marrow specimens from 101 children with pre-B ALL to examine the use of gene expression profiles (GEP) as predictors of long-term clinical outcome. Patients were divided into two cohorts for model development and validation based on availability of specimen material. Initially, GEP from 55 patients with sufficient material were analysed using HG-U133A microarrays, identifying an 18-gene classifier (GC) that was more predictive of outcome than conventional prognostic parameters. After feature selection and validation of expression levels by quantitative reverse transcription polymerase chain reaction (qRT-PCR), a three-gene qRT-PCR risk index [glutamine synthetase (GLUL), ornithine decarboxylase antizyme inhibitor (AZIN), immunoglobulin J chain (IGJ)] was developed that predicted outcome with an accuracy of 89% in the array cohort and 87% in the independent validation cohort. The data demonstrate the feasibility of using GEP to improve risk stratification in childhood ALL. This is particularly important for the identification of patients destined to relapse despite their current stratification as SR, as more intensive front-line treatment options for these individuals are already available.