The COVID-19 pandemic has highlighted the urgent need to develop reliable tools to forecast the trajectory of epidemics and pandemics in near real time. We describe and apply an ensemble n-sub-epidemic modeling framework for predicting the course of epidemics and pandemics. We systematically assess its calibration and short-term forecasting performance and compare it with other competitive statistical models. This sub-epidemic framework has demonstrated reliable forecasting performance in the context of COVID-19 and monkeypox epidemics.