This article aims at discussing a new statistical trend in research in applied linguistics. This rather new statistical procedure is causal modeling--path analysis. The article demonstrates that causal modeling--path analysis is the best statistical option to use when the effects of a multitude of L2 learners' variables on language achievement are investigated in one study. The proposed causal models, which are the property of causal modeling, provide a plausible explanation for the hypothesized relationships among the variables under inquiry. The causal modeling procedure and the statistical test of path analysis will reasonably manifest the causal relationship that naturally exists between the L2 learners' variables and are otherwise overlooked with simple correlational procedures. The paper presents a historical background on the statistical procedures involved in research about L2 learners' variables in the field of ELT. The traditional trend of linear correlation between the variables of concern can be reasonably reconsidered and replaced with the new causal modeling--Path analysis procedure. Paper also presents some rudimentary information about path analysis.