Abstract: Estimating school completion is crucial for monitoring SDG 4 on education, and unlike enrollment indicators, relies on household surveys. Associated data challenges include gaps between waves, conflicting estimates, age misreporting, and delayed completion. Our Adjusted Bayesian Completion Rates (ABC) model overcomes these challenges to produce the first complete and consistent time series for SDG indicator 4.1.2, by school level and sex, for 153 countries. A latent random walk process for unobserved true rates is adjusted for a range of error and variance sources, with weakly informative priors. The model appears well-calibrated and offers a meaningful improvement in predictive performance.