统计学上， 最小方差无偏估计（minimum-variance unbiased estimator，简写为MVUE）是一个对于所有无偏估计中，拥有最小方差的无偏估计。若无论真实参数值θ是多少，最小方差无偏估计（MVUE）都比其他不偏估计有更小或至多相等的方差，则称此估计为一致最小方差无偏估计（uniformly minimum-variance unbiased estimator，简写为UMVUE）

若 为参数函数 的一个无偏估计，且对于参数函数 的任一无偏估计 恒有下列关系　

则称 为参数函数 的一致最小方差无偏估计（UMVUE）。

In statistics a uniformly minimum-variance unbiased estimator or minimum-variance unbiased estimator (UMVUE or MVUE) is an unbiased estimator that has lower variance than any other unbiased estimator for all possible values of the parameter.

For practical statistics problems, it is important to determine the UMVUE if one exists, since less-than-optimal procedures would naturally be avoided, other things being equal. This has led to substantial development of statistical theory related to the problem of optimal estimation. While the particular specification of "optimal" here — requiring unbiasedness and measuring "goodness" using the variance — may not always be what is wanted for any given practical situation, it is one where useful and generally applicable results can be found.