INTRODUCTION: Brain metastases incidence in breast cancer women is 10-16% of all metastases. Her2neu receptor is expressed by 25% of all breast cancer cases; is considered prognostic factor for brain-metastasis development. This data and clinical stage (CS) give the proportions needed to use Montecarlo simulation model to estimate the breast cancer women proportion who will present brain metastases and the relationship with primary tumor immunophenotype. OBJECTIVES: To estimate the breast cancer women proportion who will develop brain metastasis based on probability theory METHODS: Were identified 407 women with breast cancer and were classified in: Her2neu+, hormone receptors (+), and triple negative, they were followed during 6 years and was recorded the presence of metastases and its localization. Was estimated the breast-cancer women proportion who will develop metastasis through Montecarlo method to estimate type and location of lesions using proportions for variables as: clinical stage and immunophenotype, with 405 iterations. Montecarlo simulation method was validated through ROC curve to analyze its capacity to emulate real population. RESULTS: In the real population were identified 42 (10.43%) women without clinical stage at diagnosis moment, 33 (8.15%) CSI, 192 (47.41) CSII, 118 (29.14) CSIII, and 20 (4.94) CSIV. For total patients 57.53% didn’t develop metastases, 16.54% show bone metastases, 17.78% visceral metastases, 6.17% CNS metastases and 1.98% visceral+CNS metastases. With Montecarlo simulation model the estimated data were: 53.32% women without metastases, 18.18% bone metastases, 19.16% visceral metastases, 4.42% CNS, and 4.91% CNS+visceral metastases. The correlation between estimated and observed data was 0.967 sensitivity and specificity were higher than 85%. CONCLUSIONS: Simulation Montecarlo model in resource planning and establishment of health policy for specific area could became an ancillary stone to rational resource use; with this tool the health systems could optimize economical resources to achieved medication and calculate the needs to hire more specialist or other health personnel.