I'm looking for a known design pattern or algorithm that can be used to effectively determine a set of available options to be presented to a user based on previous decisions.
An extremely simple example of this could be Year > Make > Model where Model and Make are dependent on the prior selections the user made.
I'd like this to scale to an industrial scenario like machine equipment, that can have dozens of options, each with dependencies on the prior selections the user made. I had considered a decision tree, but I felt modeling it with this many decisions could be a scalability challenge.
What would be the right learning path to pursue to build such a feature?