This paper presents a novel predictive modeling technique for yield and performance of analog integrated circuits. Trade-offs between performance functions can be explored through the use of a multi-objective evolutionary algorithm and Monte Carlo simulations. When compared to conventional simulation based approaches, the results show a significant improvement in overall simulation time and efficiency without a corresponding drop in accuracy. The behavioral model has been developed in Verilog-A and tested extensively with practical designs using the Spectre simulator. Two OTA topologies are used to demonstrate the proposed algorithm and their behavior has been verified through transistor level simulations. The examples have demonstrated that accurate performance and yield prediction can be achieved using the proposed method in a fraction of the time taken by conventional simulation based methods. Keywords—Analog circuit design, Behavioral modeling, circuit synthesis, design automation, multi-objective optimization, yield optimization.