We propose a new method, domain stabilization (DStab), to enhance the return predictive and forecasting ability of model-free option-implied moment estimators. Analyzing S&P 500 options data from January 2015 to December 2021, we show that DStab improves moment estimation consistency by stabilizing the integration domain, leading to better predictive and forecasting performance. When the options data characteristics are appropriately considered, DStab enhances both in-sample predictive and out-of-sample forecasting abilities of implied moments. DStab’s out-of-sample forecasting ability surpasses other treatment methods.