In scientific analyses, measurement errors in data can significantly impact statistical inferences, and ignoring them may lead to biased and invalid results. This study focuses on the estimation of the residual extropy function, in the presence of measurement errors. We developed an estimator for the extropy function and established its asymptotic properties. A comprehensive simulation study evaluates the performance of the proposed estimators under various error scenarios, while their practical utility and precision are demonstrated through an application to a real-world data set.