The Rao-Blackwell theorem is a fundamental result in statistics that provides a method for improving an estimator. It states that if you have an unbiased estimator of a parameter, you can create a new estimator that is at least as good, and often better, by conditioning on a sufficient statistic. This new estimator will have a lower variance, making it more efficient. In practical terms, the theorem helps statisticians refine their estimates by using additional information from the data. By applying the Rao-Blackwell theorem, one can ensure that the resulting estimator is optimal in the sense of having the smallest possible variance among all unbiased estimators.