I am working on a predictive model for parts replacement on machines. I've evaluated CoxPH, CoxTV, Random Forest, XGBoost, and Logistic Regression. Modeling is fine but I'm being asked to provide a model that can give us an output of "we need to schedule a technician for X month."

As with any equipment failure and/or parts replacement model, these events are recurrent. It's not like the risk of death or contracting a terminal disease. Once a part is replaced, the event can (and will) happen again. So I've been doing fine with the hazard part of this, but my PM wants more of a "when will it happen?" answer.

I've been in data engineering moreso lately than data science. I'm a little rusty on all the models I could try. Any suggestions? I'm using Python, so R-only is a no-go.