ZnO nanowires have been widely studied due to their unique material properties and many potential applications in electronic and optoelectronic devices. Many growth processes have been developed to synthesize ZnO nanowires. It is critically important to develop predictive process models so as to maximize the output of the nanowire synthesis. Here we report a method to characterize, quantify, and model a catalyst-free carbon-assisted ZnO nanowire growth process. Two key factors were identified for the synthesis conditions, which are reaction temperature and flow rate. Based on a factorial design method, we conducted experiments with different combinations of the two factors to study their effects on the process output (i.e. density of the nanowires), which was evaluated by a scanning electron microscope (SEM). The experimental results were analyzed using ANOVA test, and then a semi-empirical model was built to correlate the ZnO nanowire output with synthesis conditions. This model was able to describe the ZnO nanowire density with respect to synthesis conditions, which can provide guideline for synthesis parameters selection and process optimization.