The invention provides a genetic algorithm based selection method of a data model training sample. The distribution distance and distribution uniformity of samples are utilized to quantify the selection indexes that describe a training sample, the selection indexes are taken as fitness functions; a genetic algorithm is utilized to realize intelligent search of an optimal training sample, the largest working condition of sampling covering is obtained, and basis is provided for the construction of a high precision data model.