In many cases, a single view of an object may not contain sufficient features to recognize it unambiguously. This paper presents a new on-line recognition scheme based on next view planning for the identification of an isolated three-dimensional (3-D) object using simple features. The scheme uses a probabilistic reasoning framework for recognition and planning. Our knowledge representation scheme encodes feature based information about objects as well as the uncertainty in the recognition process. This is used both in the probability calculations as well as in planning the next view. Results clearly demonstrate the effectiveness of our strategy for a reasonably complex experimental set.