The invention discloses a metering device clock error trend prediction method based on a time sequence evolution gene model, and relates to the field of electric power operation and maintenance. Existing work can only solve the clock error problem of a specific scene and is not universal enough. According to the invention, a time sequence evolution gene model is adopted, the time sequence evolution gene model divides an ammeter clock error into a plurality of sub-sequences on a certain window, the model can analyze the characteristics of window sub-sequence error change, and the sub-sequenceswith similar distribution are divided into blocks through a classifier of the model; through the generative adversarial network, genes generating the subsequence distribution characteristics are mined; and combining genes of each subsequence in history, analyzing an evolution process through a recurrent neural network, analyzing an evolution mode of the subsequence, and predicting a future clock error trend of the subsequence. The technical scheme is not limited to specific devices and causes of errors, and can be adaptive to different scenes, so that a more universal scheme is provided, and the clock error problem of the generalized electric energy device is solved.