Experimental results on a variety of standard datasets show that our simple approach outperforms existing sophisticated techniques by selecting fewer features and achieving lower error rates in almost all test datasets. This suggests that feature selection for neural nets might not be as dicult as previously considered. This paper also reports two successful applications of our approach in real-world helicopter maintenance data mining applications.