TCP is one of the fundamental components of the Internet. The performance of TCP is heavily dependent on the quality of its round-trip time (RTT) estimator, i.e. the formula that predicts dynamically the delay experienced by packets along a network connection. In this paper we apply multi-objective genetic programming for constructing an RTT estimator. We used two different approaches for multi-objective optimization and a collection of real traces collected at the mail server of our University. The solutions that we found outperform the RTT estimator currently used by all TCP implementations. This result could lead to several applications of genetic programming in the networking field.