Predicting pipe failure

A system for prioritized pipe replacement, including of pipes that have never leaked, incorporating predicting pipe leaks including for pipes that have never leaked, in a network of underground pipes for carrying fluid to consumers, the system comprising:

• a database that stores a first set of variables relating to leakage of the pipes, the first set of variables being at least 60 variables;
• wherein at least some of the variables of the first set include data pertaining to pipes which have never leaked;
• and
• a processing system configured to automatically:
• select a second set of variables being a subset of the first set of variables;
• build a model using machine learning based on the second set of variables;
• predict likelihood of pipes segments leaking based on the model;
• form a graphical depiction of the pipes in said network and of likelihood of failure thereof over a selected future time period and of prioritization of pipe replacement jobs;
• and
• display said graphical depiction of pipes in said network and of likelihood of failure thereof over the selected future time and prioritization of pipe replacement jobs for carrying out pipe replacement, and
• prioritize the replacement of pipes, including of pipes that have never leaked, consistent with and guided by said graphical depiction.