Abstract: Logistic discrimination algorithms was applied to class-imbalance problem. In this algorithm,the iterative quasi-newton method was used to solve the model parameters.Taking both the model accuracy and recall-rate into consideration, the LERM (Likelihood Estimation and Recall Metric) was constructed and the logistic discrimination algorithms for imbalance (LDAI) was designed to figure out the imbalance problems.Experimental results on 16 data sets showed that the LDAI performed significantly better than traditional logistic discrimination, under-sampled and over-sampled logistic discrimination on the properties of recall-rate,f-measure,g-mean and so on.