Goji berry and buckwheat are two plant resources with both medicinal and edible values, rich in various functional components. A novel functional Huangjiu was developed, using glutinous rice as the main raw material and goji berry and buckwheat as auxiliary materials to enhance their economic value and diversify the utilization of goji berry. Through single-factor experiments and response surface methodology, using alcohol content and sensory evaluation as indicators, the fermentation process parameters were optimized. Additionally, the antioxidant activity of the Huangjiu was measured, functional components and the selenium content in selenium-enriched samples were analyzed. Kinetic models for the fermentation process were established. Results showed that the optimal fermentation conditions were as follows, a mass ratio of w (goji berry:buckwheat) of 1.5∶1.0, saccharification agent addition of 0.6%, sequential inoculation with an inoculation ratio of Saccharomyces cerevisiae to Clavispora lusitaniae of 2∶1 at 48h intervals, inoculation amount of 6%, and fermentation time of 9d. Under these conditions, the resulting Huangjiu had an alcohol content of (16.28±0.19)%vol, a total ester content of (3.17±0.14)g/100mL, and a sensory score of (82.40±1.14) points, and the flavonoid content was significantly increased. Antioxidant activity tests indicated that the maximum DPPH free radical scavenging rates for goji-buckwheat Huangjiu (Z) and selenium-enriched Huangjiu (XZ) were 89.16% and 94.49%, respectively. Moreover, the organic selenium content in XZ was 0.0128mg/kg, which had a high value for selenium supplementation. Based on the fermentation conditions, the Boltzmann model was applied to establish kinetic models for total yeast population and ethanol production, and the Logistic model equation was used to establish kinetic models for total ester production and total sugar consumption. The models showed high fitting degrees between predicted and experimental values, with R² values for XZ being 0.9705,0.9984,0.9953, and 0.9964, respectively, effectively reflecting the kinetic characteristics of the fermentation process. This study aimed to provide data support for the design of industrial fermentation tanks and the intelligent control of the fermentation process. 〖