Tiller density plays an important role in attaining optimum grain yield and applying topdressing N in winter wheat. However, the traditional approach based on determining tiller density is time-consuming and labor-intensive. As technology advances, remote sensing might provide an opportunity in eliminating this7 problem. In the present paper, an N rate experiment and a variety-seeding and sowing dates experiment were conducted in Quzhou County, Hebei Province in 2008/2009 to develop the models to predict the amount of winter wheat tillers. Positive linear relationships between vegetation indices and tillers were observed across growth stages (R2, 0.25～0.64 for NDVI; 0.26～0.65 for RVI). The validation results indicated that the prediction using NDVI had the higher coefficient of determination (R2, 0.54～0.64), the lower root mean square error (RMSE, 260～350 tillers m－2) and relative error (RE, 16.3%～23.0%) at early growth stages of winter wheat. We conclude that active GreenSeeker sensor is a promising tool for timely monitoring of winter wheat tiller density.