We study a general class of bicriteria network design problems. A generic problem in this class is as follows: Given an undirected graph and two minimization objectives (under different cost functions), with a budget specified on the first objective, find a subgraph from a given subgraph-class that minimizes the second objective subject to the budget on the first objective. We consider three different criteria—the total edge cost, the diameter, and the maximum degree of the network. Here, we present the first polynomial-time approximation algorithms for a large class of bicriteria network design problems for the previously mentioned criteria. The following general types of results are presented. First, we develop a framework for bicriteria problems and their approximations. Second, when the two criteria are the same we present a “black box” parametric search technique. This black box takes in as input an (approximation) algorithm for the unicriterion situation and generates an approximation algorithm for the bicriteria case with only a constant factor loss in the performance guarantee. Third, when the two criteria are the diameter and the total edge costs we use a cluster-based approach to devise a approximation algorithms—the solutions output violate both the criteria by a logarithmic factor. Finally, for the class of treewidth-bounded graphs, we provide pseudo-polynomial-time algorithms for a number of bicriteria problems using dynamic programming. We show how these pseudo-polynomial-time algorithms can be converted to fully polynomial-time approximation schemes using a scaling technique.