The present study has attempted to predict the default events of selected Indian defaulted corporate from selected 13 sectors namely Chemicals, Construction and Engineering, Electronics, Hotels, Infrastructure, Pharmaceuticals, Plastic & Fibre, Realty, Software, Steel, Sugar, Textile and Miscellaneous and complete sample. The total sample firms included in the are 260 defaulted firms listed in the Indian stock exchange. The period of research commences from 1st April 2004 and ends at 31st March 2019. The study incorporated 3 default prediction methods namely Multiple Discriminant Analysis, Logistic Regression, and Structural Model. the study performed the advanced default projection (foreward testing) in which the potential default events have been predicted for the time horizon: from 8 years before to 1 year before or within the actual default occurrence of the selected defaulted firms from the selected sectors. The result of the Advanced Default Projection (foreward testing) study advocates the superiority of the Structural Model over the developed MDA and developed Logit model. The Structural Model adequately diagnosed the potential default events even 8 years or 5 years before the actual default occurrence that too with high accuracy. The highest accuracy levels achieved by the Structural Model are 91%, 89% and 83% for Realty, Hotels and Construction and Engineering sectors respectively. The higher accuracy levels accomplished by the MDA model are 60%, 50% and 40% for Hotels, Construction and Engineering, Sugar sectors and Complete Sample. The developed Logit model did not perform well in advanced default projection study. This developed Logit model derived only 13%, 10% and 9% accuracies for the Chemicals, Software and Infrastructure sectors for the prediction of potential default event. Rather, the developed Logit model attained very high prediction accuracy for the “Failed” category of time horizon.