Changes in butterfly phenology due to climate changes have led to the need for models based on factors other than calendar date to predict butterfly development, allowing those monitoring their populations to increase the effectiveness of field surveys. In this study, we developed two simple climatic models, one using yearly accumulated growing degree days (GDD) and the other using yearly accumulated shortwave radiation flux densities (SRAD), to determine if these variables can predict first emergence of three butterfly species with less error than an approach based on the average ordinal date of first observation at a site. Furthermore, we investigated whether combining our two models would increase our ability to predict the timing of first emergence. We determined that GDD models were better at predicting first emergence than were ordinal date models and SRAD models for all species tested; however, the actual variation among these models was so small that any additional effort required to develop GDD models would not justify their use as a replacement for the simpler ordinal date models at this time, although as climate changes they may become more useful. We also determined that combined models did not improve the ability to predict first emergence.