Charged macromolecule systems serve as a wonderful basis for the study of the fundamental physics underlying biological phenomena. They provide relatively clean, simple systems, displaying rich physics due to their many degrees of freedom, short-ranged van der Waals interactions, long-ranged Coulomb interactions, entropic contributions arising from the mobile species, and chain connectivity. The self-assembly of charged macromolecules likely played a vital role in the emergence of life through equilibrium phase behavior like liquid-liquid phase separation and complex coacervation. In this work, we study the equilibrium phase behavior of charged macromolecule systems using conventional modeling techniques, like free energy minimization using numerical methods, and modern methods, like machine learning models, when computational barriers restrict more systematic analysis. We study the pH-responsive complex coacervation between polyzwitterions and polyelectrolytes — an interesting class of complex coacervates that are found to be stable at pH values considerably different from complex coacervates formed between polyelectrolytes. Developing new theory, we probe the many physicochemical parameters to explore the characteristics of their phase behavior. We then study the microphase separation transition behavior of sequence-defined polymers, those in which can only be distinguished by their unique monomer sequence and are analogous to proteins. The influence of monomer ordering plays a well known role in the assembly and conformations of charge macromolecules. Those sequence- dependent effects are only beginning to become unraveled and a systematic molecular dynamics study faces computational barriers. A machine learning-aided study of sequence-dependent effects on charged sequence-defined polymer phase behavior is conducted. First, we train a gradient boosted decision tree model to predict the microphase separation transition from the monomer sequence. From there, we study the learned patterns from the model to provide qualitative relationships between monomer order and microphase behavior.