This paper explores the impact of CO2 emission trading on capacity planning of electric power transmission systems. Two different models for annual emission costs are assumed. The CO2 emission price is modeled as a probability density function in the transmission network planning problem. The Monte Carlo technique is deployed to simulate the CO2 emission price volatility. The transmission network planning problem is formulated as a mixed-integer optimization whose objective is to minimize the sum of annual generator operating costs and annuitized transmission investment costs over different demand levels subject to N-1 network security constraints as well as operating limits on system components. The overall problem is formulated within the framework of a linear dc optimal power flow incorporating binary decision variables to model the lumpy nature of transmission investment. A linear model of losses is also proposed and included in the dc power flow model. The proposed approach can be used to determine the most probable optimal transmission capacity. The methodology is demonstrated through case studies simulated on the IEEE 24-bus network.