  Prediction is a fundamental objective of science. It is more difficult for
chaotic and complex systems like turbulence. Here we use information theory to
quantify spatial prediction using experimental data from a turbulent soap film.
At high Reynolds number $Re$ where a cascade exists, turbulence is becoming
easier to predict as the inertial range broadens. A transition corresponding to
the emergence of a cascade at low $Re$ is detected by looking at turbulence
through prediction.
