In this exploratory study, we seek to identify the predictors of repetition or lexical variety in the translation of English reporting verbs into Russian. Using a sample of 20 literary novels from the InterCorp corpus (v.15), we fitted multiple negative binomial regression models with a random intercept. The goal was to assess how selected predictor variables—namely, the frequency of a source-text verb, its number of senses, semantic type, length in characters, date of translation, and translator—affect the response variable: the number of Russian target-text reporting verbs an English source-text (ST) reporting verb is translated into. The findings showed that the semantic category of a ST reporting verb, its frequency and translation date as well as the translator as a random intercept have the largest individual contributions to explaining the proportion of variation in the response variable. More precisely, the model allows us to explain 73% of the variation (per conditional r-squared) in the number of distinct target text (TT) reporting verb types a ST verb is translated into. Viewed in the context of prevailing stylistic norms in Russian, the findings offer an attempt at explanation for the translator’s choices in rendering recurring reporting verbs following dialogues, which play an important stylistic effect in literary texts.