A statistical method for testing the equivalence between batches regarding their stability is proposed. This method is based on the statistical linear model making use of a set of dummy variables to code the different batches. The method gives us the point estimates of the slope and zero intercept of one batch, and the differences and the corresponding confidence intervals with the remaining batches. In a second step, zero intercepts and slopes are estimated for all the batches. Stability equivalence assessment is based on the comparison of the confidence intervals for the differences between batches with the maximum difference allowable. The main advantages of this method are the possibility to compare several batches, to disclose the equivalence stability criteria from the statistical hypothesis about the equality between slopes, and the joint estimated of the residual variance whatever the decision to pool or not the data from different batches. This method is illustrated with two data set; the first one, previously published by other authors, involved six batches; the second data set include two batches and arose in a stability study of a commercial human insulin conducted in our laboratory.