The paper investigates automatic methods of docu-ment date estimation. The document date is essential metadata for many applied tasks, such as event detection or internet search. Methods for estimating the dates of newspaper articles are well known. In this paper, we propose to predict the publishing year for scientific papers. We present a new dataset based on open access articles from eLIBRARY.RU. It contains articles written in Russian and English. The article introduces a method of dating documents based on the raw document text content. The computational experiment compares different solutions for document date estimation. We also analyze how prediction depends on the topic for different methods.