Understanding and extending the predictability of El Niño‒Southern Oscillation (ENSO) has been an important research topic because of ENSO’s large influence on global weather and climate. Here, we develop an empirical model of tropical atmosphere-oceaninteractions that has high ENSO prediction skill, comparable to the skills of well performing dynamical models. The model is used to investigate the effects of the main atmosphere-oceaninteraction processes―thermocline and zonal wind feedbacks and zonal wind forcing―on its ENSO predictability. We find that all these processes significantly affect ENSO predictabilityand extend the predictability limit by up to four months, with the largest effect coming fromthe thermocline feedbackfollowed by the total zonal wind forcing.The other processes with progressively smaller effects are thezonal wind feedbackand external zonal wind forcing.The two most influential processes, however, affect ENSO predictability in the VAR model differently. The thermocline feedback improves the forecast skill by predominantly maintaining the correct phase, whereas the total zonal wind forcing improves the skill by maintaining the correct amplitude of the forecast ENSO events. This result suggests that the dynamical seasonal prediction models must have good representations of the major ENSO processes to make skilful ENSO predictions.