In the world of growing energy demand, perovskite materials have emerged as a favorable alternative for next-generation solar cell devices owing to their high power conversion efficiency. The perovskite family is rich in multitudes, and the probability of discovering new and exciting photovoltaic materials are high. To date, most studies on this topic are focused around methyl and ethyl lead iodide structures. Recent advancement in the field of high throughput methodologies have paved a way towards the pursuit of new perovskite complexes beyond the conventional structures, facilitating an understanding of the basic physiochemical properties of these materials. Inverse Temperature Crystallization (ITC) methods were adapted to be compatible with robotic liquid-handler syntheses, resulting in the growth of large single crystals while maintain a high reaction throughput. Chemical spaces were mapped in several related systems and a large reaction dataset was generated for use with machine learning algorithms. A novel approach to prepare and characterize robot-ready perovskite crystals is described for lead halide perovskites.