Predictive Determination is the principle that each closed relational domain forecasts the shape of its successor.
Predictive Determination formalizes that each closed relational domain exposes implicit dynamics that compel the emergence of a new domain, and moreover that the architecture of the closing domain enables the system to forecast the necessary shape of its next formal extension. Closure does not merely reveal that something further is needed — it specifies what kind of thing is needed.
This is visible throughout the derivation: Coherence (step 1) does not merely leave something undetermined — it specifically leaves undetermined how coherence is sustained, which forecasts Relating. Closure (step 3) specifically leaves undetermined what distinguishes the unit from its outside, which forecasts Bounding. Each step’s residual undetermination is precise enough to predict the next step’s character.
Together with Recursive Domain Unfolding, Predictive Determination establishes that the derivation is not a series of ad hoc additions but a self-generating sequence: each domain closes in a way that both requires and specifies the next.