Language dominance is a multidimensional construct comprising several distinct yet interrelated components, including language proficiency, exposure and use. The exact relation between these components remains unclear. Several studies have observed a (non-linear) relationship between bilingual children’s amount of exposure and absolute proficiency in each language, but our understanding of the relationship between language exposure and use and relative proficiency is limited. To address this question, we examined whether experiential-based measures of language dominance, operationalised here in the narrow sense of relative language proficiency, can provide an efficient alternative to the more labor-intensive performance-based measures often used in the literature. In earlier work, Unsworth (a) examined the relationship between relative proficiency and language exposure and use in a group of English–Dutch bilingual preschool children residing in the Netherlands. This study expands these findings by examining Dutch–English preschool children of the same age residing in the United Kingdom in order to cover the full dominance continuum. Participants were 35 simultaneous bilingual children (2;0–5;0) exposed to English and Dutch, 20 resident in the Netherlands and 15 in the United Kingdom. Relative amount of language exposure and use were estimated using a parental questionnaire. To obtain performance-based measures of language proficiency, children’s spontaneous speech was recorded during a half-hour play session in each language. The transcribed data were used to derive MLU (words), average length of the longest five utterances, the number of different verb and noun types. Single word vocabulary comprehension was assessed using standardized tests in both languages. Following Yip and Matthews (2006), relative proficiency was operationalised using differentials. In line with Unsworth (2016a), English-dominant children typically had less than approx. 35% exposure to Dutch and used Dutch less than approximately 30% of the time. Curve-fitting analyses revealed that non-linear models best fit the data. Logistic regression analyses showed that both exposure and use were good predictors of dominance group membership assigned using the same approach as Unsworth (2016a), that is, using SDs. Dominance groups derived independently using cluster analyses overlapped with the groups derived using SDs, confirming that relative amount of exposure and use can be used as a proxy for language dominance.