The Organisation for Economic Co-operation and Development has published a working paper presenting a framework that combines machine learning forecasts of market income with EUROMOD tax and benefit microsimulation. Designed to address the 12 to 18 month lag in EU income statistics, the framework produces estimates of disposable income inequality and poverty for EU member states and forecasts up to four years ahead. It can also model how prospective tax and benefit reforms would affect income distribution under forecast macroeconomic conditions. The preferred approach applies LASSO based adjustments to market income by decile and reruns EUROMOD to capture taxes, benefits and automatic stabilizers. In pseudo out of sample testing, LASSO and Elastic Net models roughly halved one year mean absolute errors for the Gini coefficient compared with ordinary least squares benchmarks, recording errors of 0.006 to 0.007 versus 0.011 to 0.013. Their advantage persisted over three years, although performance varied by country and errors were greater at the top and bottom of the income distribution. A labour market adjustment module, which simulates movements into and out of employment, improved predictions of poverty dynamics more consistently than forecasts of overall inequality. The framework remains constrained by a short 2006 to 2024 estimation sample, fixed base year income deciles, the absence of broader behavioral responses and reliance on tax and benefit rules available in EUROMOD. Its validation also uses the latest macroeconomic data vintage, which may incorporate revisions unavailable at historical forecast dates.