Using bankruptcy filings under the new Insolvency and Bankruptcy Code (2016), we investigate the effect of firm characteristics and balance sheet variables on the forecast of one-year-ahead default for Indian manufacturing firms. We compare traditional discriminant analysis and logistic regression models with state-of-the-art variable selection technique-the least absolute shrinkage and selection operator, and the unsupervised techniques of variable selection-to identify key predictive variables. Our findings suggest that the ratios considered as important by Altman (1968) still hold relevance for the prediction of default, no matter the technique applied for variables selection. We find cash to current liability (a liquidity measure) as an additional robust and significant predictor of default. In terms of predictive accuracy, the reduced-form multivariate discriminant analysis model used in Altman (1968) performs at par with the more advanced econometric specification for both in-sample and full-sample default prediction.