This project is to study the function of polymeric biomaterial networks using probability analysis or simulations. The goal of this project is to understand the behavior of these networks in different formation solutions and ultimately develop a predictive model which explains how the ratio of raw material effects the decay function of average cross-link distance and lost mass over time. There are multiple steps to achieve this goal: 1. Use physical and chemistry characteristic of raw material and polymer to deduce some rules of formation. 2. Propose the probability model of polymeric formation 3. Simulate the model on the computer and see whether it confirm the data of mass lose ratio and initial average cross-link distance 4. Based on this probability model, create the decay probability model 5. Simulate the model and use machine learning to decide its parameters to fit the function of experiment data of mass lost function and average cross-link distance function.