This work examines the impact of cross- linguistic transfer on grammatical errors in English as Second Language (ESL) texts. Using a computational framework that for- malizes the theory of Contrastive Analy- sis (CA), we demonstrate that language specific error distributions in ESL writ- ing can be predicted from the typologi- cal properties of the native language and their relation to the typology of English. Our typology driven model enables to ob- tain accurate estimates of such distribu- tions without access to any ESL data for the target languages. Furthermore, we present a strategy for adjusting our method to low-resource languages that lack typo- logical documentation using a bootstrap- ping approach which approximates native language typology from ESL texts. Fi- nally, we show that our framework is in- strumental for linguistic inquiry seeking to identify first language factors that con- tribute to a wide range of difficulties in second language acquisition