Banking crises have been showing a great damage to the global economic since 1970. Since then there have been many papers trying to find out the main causes and formulate the early warning model to avoid its recurrence. Following the same purpose, this research is trying to construct an early warning system for banking crisis by combining signal approach and panel logit method. The data set is divided into two sets, in-sample and out-sample data sets. In-sample data set is used for model construction, and out-sample data set is used for the model validation. The empirical results show that real exchange rate change, export, stock index, M2 multiplier, and commercial bank deposit have significant effects on the occurrence of banking crisis, which corroborate the past results. The panel logit model with variables filtered through signal approach has better prediction power than the four indexes constructed from the signal approach for the out-sample data. The proposed model can be of great help to avoid the occurrence of banking crisis for the authorities in the practical sense.