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, were all distributed in probability form, which enabled the simulation process to reflect the uncertainty of each parameter. The Monte Carlo simulation method was used to calculate the production capacity prediction results, making the prediction results more accurate. The expected probability of production capacity was based on the statistical results of 10 000 Monte Carlo simulations, and the expected value of the production capacity index was ultimately generated as the prediction result. The method was applied to predict production capacity in an oilfield in the western South China Sea. The relative error between actual production capacity and production capacity predicted by the model was 6.3%, and the predicted results were consistent with the actual production capacity. Research has shown that pressure logging while drilling and nuclear magnetic logging 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 oilfields.