Abstarct: Modeling is one of the best tools for making decisions and solving real problems, and this technique is also used for decision making in mining operations. Solving any problem that requires decision-making can be classified into various types of operational research problems. Today, decision-making methods have changed significantly. The complexity, the high cost of operations and the extent of organizational structures make it clear to managers the need for appropriate methods of reasoned decision-making. What managers need more than anything else is a practical, reliable and appropriate tool to help them make decisions. Quantitative techniques and applied mathematical tools are used in this field. This research is in the field of studying and identifying the quantitative and qualitative amount of extractable iron ore reserves in mines and on the other hand the needs of iron ore concentrate plants. The presentation of the model has been done with the aim of providing raw materials for iron ore concentrate plants, taking into account the uncertainty of iron ore grades in mines and making decisions about appropriate allocation. First, the exploratory data of the mines have been collected and analyzed. Mineral modeling and estimation of the amount of extractable minerals has been done using the block model. The uncertainty of grade in the block model has been investigated using the Gaussian simulation method. On the other hand, the raw materials required by the plants for the production of iron concentrate during a period of 5 years have been considered according to the capacity of the plants. baxsed on iron ore type constraints, extraction capacity, grade uncertainty, quality specifications, supply and other constraints in mines and on the other hand quantitative, qualitative and demand constraints in plants, using linear planning and transportation problem and Allocation, modeling is done. At the end, by solving the problem, the tonnage of iron ore sent from each origin (mine) to each destination (plant) considering the uncertainty of the grade is presented with two approaches without considering the intermediate dump and considering the intermediate dump. The quality characteristics of the input feedstock before and after the presentation of the model in plant number one increased from 42.15% to 45.61%. The quality characteristics of the input feedstock in plant number two increased from 42.44% to 45.19%, in plant number three from 40.24% to 45.53%, and in plant number four from 39.47% to 42.4%. The presentation of this model shows that the efficiency of plants has improved by at least 6% and at most 11%.