The invention discloses a condition assessment method of an electric energy measuring device. The method includes the steps that target user measuring data is preprocessed to form a sample set, wherein the sample set includes an independent variable X and a dependent variable Y; a partial least squares regression model is established for the dependent variable Y; the partial least squares regression model is compared with a dependent variable theoretical calculation equation to obtain a condition monitoring result. The method is capable of quickly recognizing and simply assessing operation conditions of the electric energy measuring device.