Burr type XII distribution (BXIID) has earned more attention in the fewpast decades because of the flexibility of distribution shape for model fitting. However,no analytical closed formula solutions of the maximum likelihood estimates (MLEs) ofBXIID parameters can be obtained based on progressively type I interval-censored (PTIIC)samples. In this manuscript, the differential evolution algorithm (DE) and quasi-Newtonmethod (QN) are applied to searching the MLEs of BXIID parameters based on PTIICsamples. The performance of DE and QN is evaluated by means of Monte Carlo simu-lations. Simulation results show that the DE outperforms QN in terms of smaller biasand mean squared error (MSE) of the MLEs.