The problem of uncertain and/or incomplete information in information tables is addressed in the paper, mainly as far as the induction of classification rules is concerned. Two rule induction algorithms are introduced, discussed and tested on a number of benchmark data sets. Moreover, two different strategies for classifying objects on the basis of induced rules are introduced.