Studies in bilingual lexical processing employing masked translation priming with lexical decision tasks (LDT) report a priming asymmetry (larger translation priming effects in the L1 prime-L2 target direction as compared to the opposite direction). This potentially reflects a difference in the L1 and L2 primes’ ability to influence the processing of their translation targets, whereby L1 primes activate their related targets more effectively than the L2 primes. The Revised Hierarchical Model (RHM; Kroll and Stewart, 2010), explains the asymmetry by differential access to semantic information for L1 and L2 words. Comparatively weaker lexical/conceptual links for L2 words hinder their direct access to shared conceptual nodes (at least at low proficiency). Therefore, in masked translation priming studies, non-cognate L2 primes are unable to stimulate the shared semantic nodes and, in turn, to activate their L1 translation equivalents. Enhanced L2-L1 priming effects are predicted with increased L2 development (e.g., higher L2 proficiency, more exposure to the L2, etc.). Under the Multilink model’s (Dijkstra et al., 2019) tenets, the asymmetry is caused by comparatively lower subjective word frequencies (i.e., how often a word is encountered/used by each individual) in the case of L2 primes, which result in slower processing of these words, preventing them to potentially spread bottom-up activation all the way to the conceptual level under masked priming conditions. Certain individual- and stimulus-level factors (e.g., L2 proficiency, L2 exposure/use, or word frequency) might accurately serve as proxies for subjective word frequency, therefore modulating L2-L1 priming effects. Crucially, a potential effect of word frequency would allow disentangling the predictions of the two models, since Multilink alone would be able to explain this outcome. To examine these accounts, we tested 60 late sequential L1 Spanish-L2 English bilinguals living in an L2-dominant environment in a masked translation priming LDT. A 500 ms mask was followed by a 60 ms prime, immediately followed by the target (Figure 1; see Figure 2 for stimuli examples). Two individual-level factors, the participants’ L2 proficiency (i.e. upper intermediate to upper advanced) and amount of L2 exposure/use (the participants used the L1 more than the L2), and a stimulus-level predictor (word frequency) were examined and treated as continuous variables in linear mixed effects models (Baayen, 2008). This approach attempted to weigh the role that these factors have in shaping cross-language masked priming, both individually and in interaction with each other, thus addressing the dearth of data from studies on the priming asymmetry where these factors are treated continuously and in combination with word frequency. Our results do not replicate the priming asymmetry (Figure 3) (L1-L2: 39 ms; L2-L1: 50 ms, difference not significant). Response times in the critical condition were significantly faster than those in the baseline condition in both translation directions, suggesting that the related primes were able to be processed efficiently and activate their targets. Crucially, the L2-L1 priming effects were modulated by a significant effect of L1 target frequency, whereby priming was larger in more difficult trials (i.e., responding to less frequent L1 targets). We argue that it is precisely in those slower trials (i.e., those taking more time to respond to), where a “window of opportunity” opens for the L2 primes, which are allowed more time to be processed and exert an influence on the processing of their targets. Two additional trending effects of L2 prime frequency and amount of L2 exposure/use were observed in this direction. Unexpectedly (and against the RHM’s main prediction), L2 proficiency did not modulate the priming effects in any direction. These results provide support for models, like Multilink, which predict differences in the speed of lexical access to both L1 and L2 words as a function of (subjective) frequency, which may be approached through both stimulus-level and individual-level factors. Our research suggests that future work should aim at a better understanding of how, and to what extent, currently available measures capture these individual-level factors.