Many applications require predictions with confidence. We are interested in Confidence Machines which are algorithms that can provide some measure on how confident they are that their output is correct. Confidence Machines are quite general and there are many algorithms solving the problem of prediction with confidence. As predictors we consider Venn Probability Machines and Conformal Predictors. Both of these algorithms rely on an underlying algorithm for prediction and in this paper we use two simple algorithms, namely the Nearest Neighbours and Nearest Centroid algorithms. Our aim is to provide some guidelines on how to choose the most suitable algorithm for a practical application where confidence is needed.