Accurate costing provides insightful information to any Internet Service Provider (ISP) for better network planning, profits, and decision making. Developing accurate cost models for communication network services has always been a challenge for ISPs / cloud operators due to the complex nature of today's advanced shared cloud and network infrastructure. Currently, developing and maintaining such cost models require significant effort and time by the network planners in an ISP. The proposed novel methodology reduces the cycle time for the development of the cost model significantly, which leads to the ISP's operational cost savings. We have considered an Internet Protocol Virtual Private Network (IPVPN) service for the study. IPVPN creates a logical virtual network by providing an encrypted and dedicated data connection. We conducted simulations to validate the accuracy and effectiveness of the proposed model. We have compared our proposed method with the existing approach and compute the performance improvement cost gap for different network sizes. To prove the operational savings, we evaluated a quantitative example concerning both methods investigated. We also experimented with a machine learning technique for the study, which provided complementary results.