We consider the problem of recognizing a particular target of interest (i.e. the "correct" target) while rejecting other targets and background clutter. In such instances, the probability of recognizing the correct target (PCT) is a suitable metric for assessing the performance of the target recognition algorithm. We present a definition for PCT and illustrate how it differs from conventional metrics for target recognition by means of an example. It is further shown that an adaptive target recognition algorithm, which relies on track position to obtain multiple looks at the target, can significantly improve PCT while reducing the track uncertainty.