Sunyaev-Zeldovich (SZ) surveys are promising probes of cosmology - in particular for Dark Energy (DE) -, given their ability to find distant clusters and provide estimates for their mass. However, current SZ catalogs contain tens to hundreds of objects and maximum likelihood estimators may present biases for such sample sizes. In this work we use the Monte Carlo approach to determine the presence of bias on cosmological parameter estimators from cluster abundance as a function of the area and depth of the survey, and the number of cosmological parameters fitted. Assuming perfect knowledge of mass and redshift some estimators have non-negligible biases. For example, the bias of $sigma_8$ corresponds to about $40%$ of its statistical error bar when fitted together with $Omega_c$ and $w_0$. Including a SZ mass-observable relation decreases the relevance of the bias, for the typical sizes of current surveys. The biases become negligible when combining the SZ data with other cosmological probes. However, we show that the biases from SZ estimators do not go away with increasing sample sizes and they may become the dominant source of error for an all sky survey at the South Pole Telescope (SPT) sensitivity. The results of this work validate the use of the current maximum likelihood methods for present SZ surveys, but highlight the need for further studies for upcoming experiments. [abridged]
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