Conformal predictions uses past experience to determine precise levels of confidence in new predictions. Given an error probability ε, together with a method that makes a prediction of the label y, it produces a set of labels that contains y with probability 1 − ε. Conformal prediction can be applied to any method which make predictions, for instance, nearest-neighbor method, support-vector machine, ridge regression, etc. In this talk, the speaker will give a brief introduction to Conformal prediction and give several examples.