Bicycle volume data are useful to practitioners and researchers to understand safety, travel behavior, and development impacts. This paper describes the methodology used to develop several simple models of bicycle intersection volumes in Alameda County, California. The models are based on two-hour bicycle counts performed at a sample of 81 intersections in the Spring of 2008 and 2009. Study sites represented areas with a wide range of population density, employment density, proximity to commercial property, neighborhood income, and street network characteristics. The explanatory variables considered for the models included intersection site, land use, transportation system, and socioeconomic characteristics of the areas surrounding each intersection. Four alternative models are presented with adjusted R-square values ranging from 0.39 to 0.60. The models showed that bicycle volumes tended to be higher at intersections surrounded by more commercial retail properties within 1/10 mile, closer to a major university, with a marked bicycle facility on at least one leg of the intersection, surrounded by less hilly terrain within 1/2 mile, and surrounded by a more connected roadway network. The models also showed several important differences between weekday and weekend intersection volumes. The positive association between bicycle volume and proximity to retail or a large university was greater on weekdays than weekends, while bicycle facilities had a stronger positive association and hilly terrain had a weaker negative association with bicycle volume on weekends than weekdays. Further testing and refinement is necessary before accurate count predictions can be made in Alameda County or other communities.