In this paper, neutral networks are used to build models of oxide film etched In CHF$_3$/CF$_4$ with a magnetically enhanced reactive ion etcher(MERIE). A statistical 2$^$4-1/ experimental design plus one center point was used to characterize relationships between process factors and etch responses. The factors that were varied include radio frequence(rf) power, pressure, CHF$_3$ and CF$_4$ flow rates. Resultant 9 experiments were used to train neural networks and trained networks were subsequently tested on its appropriateness using additionally conducted 8 experiments. A total of 17 experiments were thus conducted for this modeling. The etch responses modeled are dc bias voltage, etch rate and etch uniformity A qualitative, good agreement was obtained between predicted and observed behaviors.