Tone-mapping operator (TMO) plays a crucial role in the task towards displaying high dynamic range (HDR) contents on standard displays. Similarly, visual attention (VA) is a vital feature of the human visual system (HVS), while it has not been sufficiently investigated in preference of tone-mapped images. The potential benefits of visual attention-based features for quality assessment of tone-mapped images are studied in this paper. A novel framework is proposed for tone-mapped image quality assessment to predict image preference. The framework is evaluated on two different datasets. Experimental results illustrate the importance of visual attention for improving the performance of objective metrics. The proposed framework outperforms the existing methods and presents as a competitive alternative for tone-mapped images evaluation.