There has been attempts to document the effect of smiling by candidates in ballot pictures on votes for candidates. However, existing studies are plagued by confounding by comparing across candidates with differences in smiling and many other characteristics. We vastly improve over the previous studies by using an algorithm to code smiling (and beauty/feelings) in pictures of politicians in Colombian mayoral elections across several elections. This allows us to estimate the effect of smiling for the same candidate in different elections substantially removing confounding by using candidate fixed effects. Furthermore, we control for time varying confounders that could lead to candidates to change their smile across elections. After coding 8806 pictures, we find that if a candidate did not smile (smile index = 0) and later had a smile (smile index = 1), this can increase the vote share by 2.4 percentage points, which is a sizeable amount. Moreover, using measures of beauty, we explore how the effect of smiling can be boosted by candidate’s beauty. This aims to tie the separate literatures on smiling and voting, and beauty and voting, and shows how a simple smile can make a difference in who gets more votes.