The aim of this paper is to establish a dependable approach to the identification of continuous-time models from sampled data. Some equation-error structure-based methods of the CONTSID (CONtinuous-Time System IDentification) Matlab toolbox that directly estimate continuous-time transfer function models from discrete-time data are compared with some classical discrete-time model identification techniques of the Matlab System IDentification (SID) toolbox. CONTSID is equipped with tools based on the developments over the past three decades and is noncommercial. The results of extensive numerical experiments presented in this paper suggest that direct approaches, that is, those in which continuous-time models are directly identified are superior to the indirect methods in which discrete-time models are first identified and then transformed into continuous-time models. It is also clear from this investigation that for identification problems in a wider context, that is, with choice between discrete-time and continuous-time models, it is desirable to have a set of tools, whose dependability is greatly enhanced by unifying all relevant approaches.