With the progress of both photonics and electronics, optoelectronic synapses are considered potential candidates to challenge the von Neumann bottleneck and the field of visual bionics in the era of big data. They are also regarded as the basis for integrated artificial neural networks (ANNs) owing to their flexible optoelectronic tunable properties such as high bandwidth, low power consumption, and high-density integration. Over the recent years, following the emergence of metal halide perovskite (MHP) materials possessing fascinating optoelectronic properties, novel MHP-based optoelectronic synaptic devices have been exploited for numerous applications ranging from artificial vision systems (AVSs) to neuromorphic computing. Herein, we briefly review the application prospects and current status of MHP-based optoelectronic synapses, discuss the basic synaptic behaviors capable of being implemented, and assess their feasibility to mimic biological synapses. Then, we focus on the two-terminal optoelectronic synaptic memristors and three-terminal transistor synaptic phototransistors (SPTs), the two essential apparatus structures for optoelectronic synapses, expounding their basic features and operating mechanisms. Finally, we summarize the recent applications of optoelectronic synapses in neuromorphic systems, including neuromorphic computing, high-order learning behaviors, and neuromorphic vision systems, outlining their potential opportunities and future development directions as neuromorphic devices in the field of artificial intelligence (AI).