Low-temperature heat conversion is a key aspect in more sustainable and greener power production. Organic Rankine cycles, which use a refrigerant as working fluid, are one of the possible technologies on the market for this type of heat conversion. In order to improve efficiency of these cycles, these systems can be operated under supercritical conditions. In the design of the heat exchangers, the heat transfer to current and new refrigerants under supercritical conditions must thus be accurately predicted. As large property variations occur during heating of a supercritical fluid, heat transfer is influenced by phenomena such as buoyancy and flow acceleration, and cannot be predicted accurately with single-phase based correlations. In literature, several supercritical heat transfer correlations exist, however, they are mostly developed based on experimental data of vertical flow of water and CO₂. For refrigerants under horizontal flow, previously developed correlations (even if based on refrigerant data) lack accuracy and directives for which correlation should be used on which refrigerant and under what operating conditions. Therefore, in this work, a general heat transfer correlation for supercritical low GWP refrigerants for horizontal flow under heating conditions is proposed. For this purpose, relevant supercritical heat transfer data from literature are gathered and the performance of several existing heat transfer correlations is evaluated. The correlation developed by Tian et al. performs best, both for the bottom and the top of the horizontal tube, predicting 89% and 84% of the data, respectively, within a relative error below 30%. All the other correlations perform inadequately with very low performance in predicting the heat transfer on the top side of the tube. Then, the influence of certain correction factors on the performance of correlations is investigated. Both for the top and the bottom of the tube, incorporating a correction factor based on density to take into account the radial property variations improves the performance of the correlation. For the top of the tube, the performance can be further enhanced by incorporating an additional correction term Gr_b/Re² to account for buoyancy effects. Based on this analysis, two new heat transfer correlations are proposed, one for the bottom and one for the top of the tube. While the performance of the bottom correlation is comparable to the best performing one from literature, the prediction of the heat transfer on the top of the tube can be significantly improved when using the newly developed correlation as 78% of the data can be predicted within a relative error of 20% and 90% of the data within 30%.