Аннотация:This paper describes an automatic spelling correction system for Russian. The system utilizes information from different levels, using edit distance for candidate search and a combination of weighted edit distance and language model for candidate hypotheses selection. The hypotheses are then reranked by logistic regression using edit distance score, language model score etc. as features. We also experimented with morphological and semantic features but did not get any advantage. Our system has won the first SpellRuEval competition for Russian spell checkers by all the metrics and achieved F1-Measure of 75%.