  Large numbers of supernovae (SNe) have been discovered in recent years, and
many more will be found in the near future. Once discovered, further study of a
SN and its possible use as an astronomical tool (e.g., as a distance estimator)
require knowledge of the SN type. Current classification methods rely almost
solely on the analysis of SN spectra to determine their type. However,
spectroscopy may not be possible or practical when SNe are faint, numerous, or
discovered in archival studies. We present a classification method for SNe
based on the comparison of their observed colors with synthetic ones,
calculated from a large database of multi-epoch optical spectra of nearby
events. We discuss the capabilities and limitations of this method. For
example, type Ia SNe at redshifts z < 0.1 can be distinguished from most other
SN types during the first few weeks of their evolution, based on V-R vs. R-I
colors. Type II-P SNe have distinct (very red) colors at late (t > 100 days)
stages. Broadband photometry through standard Johnson-Cousins $UBVRI$ filters
can be useful to classify SNe out to z ~ 0.6. The use of Sloan Digital Sky
Survey (SDSS) ugriz filters allows the extension of our classification method
to even higher redshifts (z = 0.75), and the use of infrared bands, to z = 2.5.
We demonstrate the application of this method to a recently discovered SN from
the SDSS. Finally, we outline the observational data required to further
improve the sensitivity of the method, and discuss prospects for its use on
future SN samples. Community access to the tools developed is provided by a
dedicated website (http://wise-obs.tau.ac.il/~dovip/typing) .
