Abstract: In the process of oilfield development, it is necessary to quickly and accurately predict production capacity to provide technical support for decision-making on oilfield development plans. To this end, based on the production capacity formula and oil recovery index formula, formula parameters were set based on drilling data and adjacent well data, and a production capacity prediction model was established. The parameters such as permeability, reservoir thickness, formation volume coefficient, viscosity, and discharge radius are all distributed in probability form, which enables the simulation process to reflect the uncertainty of each parameter. The Monte Carlo simulation method is used to calculate the production capacity prediction results, making the prediction results more accurate. The expected probability of production capacity is based on the statistical results of 10,000 Monte Carlo simulations, and the expected value of the production capacity index is ultimately generated as the prediction result. The method was applied to predict production capacity in a certain oilfield in the western South China Sea. The relative error between actual production capacity and model predicted production capacity was 6.3% that the predicted results were consistent with the actual production capacity. Research has shown that pressure test while drilling and nuclear magnetic resonance while drilling data can provide valuable information for production capacity prediction models. The prediction results of this method can guide the production capacity evaluation and development decisions of subsequent development wells in the oil fields.