Refractivity from clutter (RFC) refers to techniques that estimate the atmospheric refractivity profile from radar clutter returns. A RFC algorithm works by finding the environment whose simulated clutter pattern matches the radar measured one. This paper introduces a procedure to compute RFC estimator performance. It addresses the major factors such as the radar parameters, the sea surface characteristics, and the environment (region, time of the day, season) that affect the estimator performance and formalizes an error metric combining all of these. This is important for applications such as calculating the optimal radar parameters, selecting the best RFC inversion algorithm under a set of conditions, and creating a regional performance map of a RFC system. The performance metric is used to compute the RFC performance of a non-Bayesian evaporation duct estimator. A Bayesian estimator that incorporates meteorological statistics in the inversion is introduced and compared to the non-Bayesian estimator. The performance metric is used to determine the optimal radar parameters of the evaporation duct estimator for six scenarios. An evaporation duct inversion performance map for a S band radar is created for the larger Mediterranean/Arabian Sea region.