As an important safety discharge facility in petrochemical industry, flare is widely used in offshore and onshore oil and gas fields to relieve pressure, vent unwanted gases. This open-air combustion system oxidizes the fuel gases into carbon dioxide and water vapor and hence avoids the contamination of air with harmful gases that cause air pollution and climate change. With the increasingly strict requirements of environmental protection and the implementation of low-carbon development policy, the black carbon (soot) caused by incomplete combustion from the flare will be strictly controlled. At present, there is no simple and effective method to determine whether the flare produces visible black carbon which exacerbates the pollution. According to the investigation on site, there are different degrees of black carbon emission from the flares both in the onshore and offshore oilfield, which brings some troubles to the petroleum corporation. Based on a flare tip and the associated gas from an oilfield in Bohai Bay of China, a simulation model, which in accordance with the actual situation, was established with the Computational Fluid Dynamics software. The Non-Premixed Combustion model was used to simulate the Combustion, the P-1 model was adopted to calculate the thermal radiation and the Moss-Brookes model was selected to compute the generation of black carbon. The feasibility of the model was demonstrated by comparing the simulation results with the field test results. Then the limitation of current conventional practice to predict whether the soot is produced, was demonstrated with the model. At the same time, the production rate of black carbon under different conditions of components and fraction were calculated. After a comprehensive analysis and comparison, a simple, directly and effective method to predict the soot was proposed. When the C-to-H ratio of fuel gas is greater than 0.273, it tends to visible soot, and when the C-to-H ratio is greater than 0.285, it tends to heavy soot, which is in line with the actual in site. Therefore, the method can be applied to predict the level of the generation of black carbon in the engineering.