This article presents a conceptual replication of Hashimoto and Egbert (https://doi.org/10.1111/lang.12353), a study that featured multivariate models where lexical sophistication variables accounted for word difficulty (yes-no recognition) better than frequency alone among learners of English as a second or foreign language from North America. This current study (n words = 88; n people = 128) conceptually replicated Hashimoto and Egbert with data from three Asian university English-for-academicpurposes sites. Methodological differences included a more conservative lexical sophistication operationalization process and avoidance of stepwise regression. Like the original study, the replication's findings favored multivariate models over frequency, which predicted 36% of word difficulty's variance alone. In a multiple regression model accounting for word difficulty, R 2 = .52, frequency accounted for 17% of the predicted variance with age of acquisition (AoA: 18%) and word naming reaction time (WN_RT: 16%) also being significant predictors. This replication also extended the testing approach by using a mixed-effect model, involving person and site intercepts as random effects. The model's ability to predict word difficulty fell, marginal R 2 = .22, conditional R 2 = .40, but frequency, AoA, and WN_RT remained the strongest predictors. Taken together, this replication successfully supports the original study's more-than-frequency conclusion while highlighting the need for further research into the area.