We introduce MolPhase (http://molphase.sbs.ntu.edu.sg/), an advanced protein phase separation (PS) prediction algorithm that improves accuracy and reliability by utilizing diverse physicochemical features and extensive experimental datasets. MolPhase applies a user-friendly interface to compare distinct biophysical features side-by-side along protein sequences. By additional comparison with structural predictions, MolPhase enables efficient predictions of new phase-separating proteins and guides hypothesis generation and experimental design. Key contributing factors underlying MolPhase include pi-pi interaction, disorder, and prion-like domain. As an example, MolPhase finds that phytobacterial type III effectors (T3Es) are highly prone to homotypic PS, which was experimentally validated in vitro biochemically and in vivo in plants, mimicking their injection and accumulation in the host during microbial infection. In addition, the phase-separation of T3Es were evolved both in vivo and in vitro, suggesting their determinative scaffolding function, though there is a difference in material properties, implying a difference in homotypic and heterotypic macromolecular condensation. Robust integration of MolPhase's effective prediction and experimental validation exhibit the potential to evaluate and explore how biomolecule PS functions in biological systems.