This study aims to assist in the design of the quantitative aspects of the process of infrastructure asset-backed securitization. We develop a series of optimization programs that models the bond structuring process. Targeting at toll road projects, the study focuses on modeling the cash flow distribution derived from the toll revenue, and the bond structuring design based on these cash flows. The toll revenue forecast model is formulated as a bi-level mathematical program where the upper level is to maximize the revenues from tolls by finding the optimal toll rate and the lower level is the traffic assignment problem. Then there are two optimization programs for two types of structure in bond structuring: revenue bond structure and tranche structure. The objective is to find the optimal size of issue and the corresponding coupon rate that benefit the originator the most. With the mathematical models, we are able to impose policy constraints and external risk events on the toll revenue forecast model, and risk mitigations such as reserve fund on the bond structure. The models allow us to examine the impact of those policy or risk mitigations on the design, performance and risk assessment for the bonds. We use a simple network as the numerical example to forecast its future revenue, which is the cash flow source for a single-project securitization deal.