Most patients with chronic lymphocytic leukemia (CLL) are diagnosed with early stage disease and managed with active surveillance. The individual course of subjects with early stage CLL is heterogeneous and their probability of needing treatment is hardly anticipated at diagnosis. We aimed at developing an international prognostic score to predict time to first treatment (TTFT) in CLL patients with early, asymptomatic disease (IPS-E). Individual patient data from 11 international cohorts of patients with early stage CLL (n=4933) were analyzed to build and validate the prognostic score. Three covariates were consistently and independently correlated with TTFT: unmutated IGHV genes, absolute lymphocyte count >15 x109/l, and presence of palpable lymph nodes. The IPS-E was the sum of the covariates (one point each), and separated low-risk (score 0), intermediate-risk (score 1) and high-risk patients (score 2-3) showing a distinct TTFT. The score accuracy was validated in 9 cohorts staged by the Binet system and 1 cohort staged by the Rai system. The c-index was 0.74 in the training series and 0.70 in the aggregate of validation series. By meta-analysis of the training and validation cohorts, the 5-year cumulative risk of treatment start was 8.4%, 28.4%, and 61.2% among low-risk, intermediate-risk, and high-risk patients, respectively. The IPS-E is a simple and robust prognostic model that predicts the likelihood of treatment requirement in patients with early stage CLL. The IPS-E can be useful in clinical management and in the design of early intervention clinical trials.