Suppose we have a dataset with many (~100) features and a binary outcome. I am interested in not only assessing whether any given feature is causally related to the outcome, but in actually being able to say that users X,Y,and Z got the outcome specifically because of some specific feature(s). Is this even possible? If so, could someone please give me some pointers as to go about it (math, codes, packages, etc.)?
Yes, this is the problem of "probability of causation." It is not a major topic in the causal inference literature, but there has been some written on it. A Google search led me to this CDC page on interpreting probability of causation and this paper (Dawid, Musio, Murtas, 2017) on contemporary perspectives in probability of causation. The concept is used when attempting assign blame or responsibility for an event to some causal actor.