This study aims to develop a transparent rule-based model for water sector investment planning. It will focus on identifying indicators contributing to urban pipeline failures through collaboration with domain experts. Our research objectives are as follows: 1. Revise conventional renewal rates by introducing rule-based indicators to optimize reinvestment strategies. 2. Generate interpretable rules based on the Rough sets theory to initially identify interconnected factors related to pipe failure. 3. Incorporate expert knowledge through the employment of Dempster-Shafer theory for a better understanding of the phenomenon while accounting for uncertainty and conflict. 4. Compare the model's results with traditional machine learning models to highlight the advantages of transparent models combined with expert knowledge. 5. Evaluate the integrated model's performance in identifying pipe failures and the interpretability of derived rules. By achieving these objectives, this study will contribute to developing more effective and efficient approaches to identifying and prioritizing reinvestments for municipalities and water utilities in Sweden. Moreover, fostering a sense of involvement through expert knowledge involvement can enhance collaboration and increase the likelihood of achieving practical solutions, ensuring politically feasible outcomes.