A tree-based method for censored survival data is developed, based on maximizing the difference in survival between groups of patients represented by nodes in a binary tree. The method includes a pruning algorithm with optimal properties analogous to the classification and regression tree (CART) pruning algorithm. Uniform convergence of the estimates of the conditional cumulative hazard and survival functions is discussed, and an example is given to show the utility of the algorithm for developing prognostic classifications for patients.