The work of Yalkowsky at Arizona [12] has resulted in what is now called the "generalized solvation equation." It states that the solubility of a compound can be broken into two steps, first the melting for the pure solid to pure liquid and second, the phase transfer from pure liquid into water. For many small organic molecules, this second step is somewhat related to LogP. Because of this relation we choose to explore the use of the XLogP atom-types in solubility prediction. The expectation was that this might provide an approximate though robust and fast method for calculating solubility. We fit the XLogP atom-types to a training set of nearly 1000 public solubilities. From this we derived a linear model for solubility. The model is extremely fast and is useful for classifying compounds as insoluble, poorly soluble, slightly soluble, moderately, soluble or very soluble. The model is notable for the difficulty it has predicting solubilities for compounds with ionizable groups. Further, it is not suitable for the PK predictions that come late in a project. However, it is useful for eliminating compounds with severe solubility problems early in the virtual-screening process.