We have insight into the importance of resource exploration derived from the quest for sustaining competitive advantage as well as the growth of the firm, which are well-explicated in the resources-based view. However, we really do not know when the firm will seriously commit to this kind of activities. Therefore, this study proposes intelligent approach using auto-regressive moving-average regression (ARMAX), back-propagation neural network (BPNN), or segmented adaptive support vector regression (SASVR) to constitute the relationship among five indicators, the growth rate of long-term investment, the firm size, the return on total asset, the return on common equity, and the return on sales. In such a way, the methods we build can explain the timing of resources exploration in the behavior of firm. Meanwhile, the performance between these methods is compared quantitatively.