To create a classification model to identify if an organic solvent is miscible or immiscible in water, we constructed a small water miscibility/immiscibility dataset of 26 solvents. We predicted the aqueous solubility for each of those solvents (Table ). To establish the watermiscibility cutoff value, we trained a support vector machine classifier with a linear kernel, which enables straightforward determination of the miscibility threshold as the intercept divided by the coefficient of the linear equation. To estimate the 90% confidence interval of the threshold, we performed bootstrapping, where the data was sampled with replacement 5,000 times and each time the model was fitted to subsampled data and the threshold value was obtained. Each subsample contained the same number of datapoints (26) as the original dataset. The mean of these values is the final aqueous miscibility threshold and is equal to 0.08 log(S / mol/dm 3 ). The upper and the lower bound of the 90% confidence interval were obtained by calculating the 5 th and 95 th percentiles of the threshold values, respectively. The lower bound is equal to -0.34 log(S / mol/dm 3 ) and the upper bound is equal to 0.44 log(S / mol/dm 3 ).