what forecasting method actually works best for predicting open-source adoption curves at this scale?

curious whether anyone making calls on this list is leaning on a specific methodology or just going with informed intuition. growth curves and extrapolation seem like the obvious starting points for something like github stars, but adoption in open-source tends to have nonlinear jumps tied to ecosystem events, a major framework adopting a library, a viral post, a competitor going paid, that kind of thing. those discontinuities make pure extrapolation unreliable past a certain horizon. the 2027 deadline is long enough that a lot can shift. so are people anchoring on current trajectory and adjusting for known catalysts, or is there a more structured approach being used here, something closer to analogy forecasting against projects that already crossed similar thresholds?