Algorithm for 3-object matching I believe that in the general case stable matching for 3 members rather than 2 is NP-Complete, but I wonder if in my case there's something that I am missing that could have reasonable time complexity. 

The specific purpose of the program I am trying to write is to take an arbitrary number of objects and split them into groups of 3. Hypothetically, each object has a color (let's say right now there's 10 possible colors).

The part of this group creation that allows something of a "preference list" of other members is both having group members of different colors and having been grouped with them in the past as little times as possible.

Everything I have come up with either has horrendous time complexity or has the chance of failing (missing possible groupings). If anyone has done anything like this before I would appreciate any suggestions.
It sounds like you're looking for a polynomial-time approximation algorithm for the 3-dimensional matching problem (which is, as you noted, NP-complete - the decision problem is one of Karp's 21 NP-complete problems).

In 2014, Ostrovsky and Rosenbaum proved that 3D matching is APX-complete. This implies the existence of an efficient algorithm that produces a result within a "fixed multiplicative factor of the optimal answer" - in their case, $4/9$.