There isn't a single, universally accepted term for two things that predict each other. However, depending on the specific context and the nature of the prediction, you could use various terms:

General Terms:

* Reciprocal causation: This term emphasizes that both things influence each other.

* Mutual prediction: This term focuses on the ability of each factor to predict the other.

* Interdependence: This term highlights the interconnected nature of the two factors.

More Specific Terms:

* Feedback loop: This term is used when the relationship between the two things is cyclical, meaning that each one affects the other in a continuous cycle.

* Correlation: This term describes a statistical relationship between two variables, but it doesn't necessarily imply causation.

* Co-variation: Similar to correlation, this term indicates that the two variables change together, but it doesn't explain why.

Example:

Imagine a situation where low levels of social interaction predict increased loneliness and increased loneliness predicts lower levels of social interaction. You could describe this relationship as a feedback loop or a reciprocal causation between social interaction and loneliness.

Ultimately, the best term to use will depend on the specific context and the nature of the relationship you are describing.