Population balance equations (PBE) coupled with mass and energy balance equations represent the common modeling framework for crystallization processes. Often the expressions required for crystal growth, nucleation, as well as aggregation and breakage rates contain parameters that need to be estimated from experimental data. To establish a process model, parameter estimation (PE) is applied to determine an optimal set of parameters by minimizing the sum of squared errors between the experimental results and the model output. Inappropriate selection of the objective function, the optimization routine itself and inaccurate or limited experimental data might severely handicap the parameter estimation procedure. In this study, the sensitivity of parameter estimation concepts is investigated. Therefore the limits of multiple optimization algorithms (global and local ones) and the consequence of limited or inaccurate experimental data were analyzed in detail. Furthermore the present work discusses how oversimplified model assumptions affect the interpretation of experimental results and exposes pitfalls in the interpretation of parameter estimation results. (C) 2014 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.