Puttick et al. (2017; Proc. Roy. Soc. DOI: 10.1098/rspb.2016.2290) performed a simulation study to compare accuracy between methods inferring phylogeny from discrete morphological characters. They report that a Bayesian implementation of the Mk model (Lewis, 2001) was most accurate (but with low resolution), while a maximum likelihood (ML) implementation of the same model was least accurate. They conclude by strongly advocating that Bayesian implementations of the Mk model should be the default method of analysis for such data. While we applaud investigations into accuracy and alternative methods of analysis, this conclusion is based on an inappropriate comparison of the ML point estimate with the Bayesian consensus. We revisit these issues through simulation by considering uncertainty in ML reconstructions, and demonstrate that Bayesian and ML estimates are generally concordant when conventional edge support thresholds are considered. We therefore disagree with the conclusions of Puttick et al. (2017), and consider their prescription of any default method to be unfounded. Instead, we recommend caution and thoughtful consideration of the model or method being applied to a morphological dataset.