The red wine fermentation needs fast and nondestructive techniques, which can help to control the fermentation process and assure the quality of wine. In the present study, near infrared spectroscopy (NIR) and electronic nose (EN) were used to predict the alcohol content during the red wine alcoholic fermentation. Calibration models were developed between instrumental data and chemical analysis using principal component regression (PCR) and partial least squares regression (PLSR) with cross validation. Good correlations (R>0.99) were acquired for both the models developed by the NIR and EN data. However, RMSEC and RMSEP were a little larger. Combining NIR and EN can optimize the model and improve the prediction accuracy. The PLSR model based on combined data shows the best correlation (R=0.999 2), with RMSEC and RMSEP being 0.206 and 0.205% (v/v), respectively. Both NIR spectroscopy and EN can predict the alcohol concentration during the alcoholic fermentation of red wine, and the combination of two instruments can improve the analysis precision. Although the measurements were carried out in off-line mode, this study demonstrates that NIR and EN can be used as on line, fast, nondestructive and in time techniques to provide in-time information about the fermentation process and to assure the quality of final products.