Abstract: Based on the statistical data about basic situation of papers published in per issue among 36 issues in 3 years of Materials for Mechanical Engineering journal,the predicting model for the relation between per issue quality of the scientific and technical periodical and 3 evaluation factors which were paper quantity,rate of articles supported by foundations and rate of authors from academe and universities had been developed with back propagation (BP) artificial neural network method,and the extent of the influence caused by the factors on per issue quality of scientific and technical periodicals had been analyzed.The results show that it is feasible to evaluate the per issue quality of the scientific and technical periodicals by BP artificial neural network method,and the model which can primely evaluate the practical quality of per issue is worth of spreading and popularizing for the quality evaluation of scientific and technical periodicals,especially for the pre-evaluation of per issue quality of the scientific and technical periodicals before publication.The main influencing factor on per issue quality of scientific and technical periodicals is paper quantity,and the next ones whose influence degree are about the same are rate of articles supported by foundations and rate of authors from academe and universities.