The present application discloses a frontpage news prediction and classification method. Keywords to be queried are firstly input by means of a user interface, and collected news text information on the web pages is saved in a local database; a text representation module performs vector representation by using a Doc2Vec representation algorithm, so as to convert each news text into a low-dimensional text feature vector with a high amount of information; and a similarity network construction module calculates the similarity between news, constructs a news similarity network by taking a calculated similarity matrix as an adjacent matrix of a news related network, determines whether a similarity network is traversed, if so, iteratively calculates an HR value of the vector according to an H-index supporting contribution matrix, performs weight sorting on the news by using the HR value, and predicts top-N pieces of news as front page news.