The invention relates to a transformer maintenance optimization method based on the symbol dynamics and the LS-SVM. Basic data are segmented in an abstract mode to obtain five variable quantities, namely, the defect distribution change, the fault distribution change, the environment change, the load change and the maintenance plan change of a transformer through an item on the basis of a symbol dynamics method, and symbol description is conducted on the five variable quantities. Benefit gains and outage cost generated before and after maintenance scheme adjustment are calculated according to the LS-SVM algorithm through the combination with defect data over the years and the influences of the maintenance scheme on defects, and therefore the optimal maintenance scheme is obtained. The transformer maintenance optimization method has the advantages that different types of factors with different time variants and complex mutual relations are described through the symbol dynamics; the LS-SVM learning capacity and the fitting effect are improved; the transformer risk change law is obtained by conducting modeling analysis and prediction through the LS-SVM, and therefore the problems that an existing maintenance optimization method is low in prediction efficiency and not ideal in effect under the condition of a small sample, is easily caught in the local extremum, and the like are solved.