Colour preference is a critical dimension for describing the colour quality of lighting and numerous metrics have been proposed. However, due to the variation amongst psychophysical studies, consensus has not been reached on the best approach to quantify colour preference. In this study, 25 typical colour quality metrics were comprehensively tested based on 39 groups of psychophysical data from 19 published visual studies. The experimental results showed that two combined metrics: the arithmetic mean of the gamut area index (GAI) and colour rendering index (CRI) and the colour quality index (CQI), a combination of the correlated colour temperature (CCT) and memory colour rendering index (MCRI), exhibit the best performance. Qp in the colour quality scale (CQS) and MCRI also performed well in visual experiments of constant CCT but failed when CCT varied, which highlights the dependence of certain metrics on contextual lighting conditions. In addition, it was found that some weighted combinations of an absolute gamut-based metric and a colour fidelity metric exhibited superior performance in colour preference prediction. Consistent with such a result, a novel metric named MCPI (colour preference index based on meta-analysis) was proposed by fitting the large psychophysical dataset, and this achieved a significantly higher weighted average correlation coefficient between metric predictions and subjective preference ratings.