<p>Remote sensing (RS) technologies have increasingly become essential in mapping mineral resources, as they offer innovative and cutting-edge solutions crucial for detecting and comprehensively assessing mineral deposits across diverse geological settings. This in-depth review thoroughly explores several prominent and newly emerging trends, encompassing significant advancements in satellite imagery, strategic combination of artificial intelligence (AI) and machine learning (ML) methodologies along with relevant case studies, the use of Light detection and ranging (LiDAR), RADAR (Radio Detection and Ranging) systems, drone and unmanned aerial vehicles (UAVs), real time data analysis and data fusion techniques. These sophisticated technologies markedly enhance the efficacy and accuracy of data collection, processing, and analysis, ultimately facilitating the formulation and execution of more effective exploration strategies that can considerably diminish the time and resources necessary for successful mineral exploration. Unlike previous reviews, we synthesize these trends to chart the evolution towards predictive mineral systems modeling, identifying key challenges and future pathways for the industry. By addressing both the innovative features and the constraints of remote sensing (RS) technologies, this analysis seeks to present a balanced viewpoint that enriches the ongoing dialogue regarding their future role in mineral resource exploration. Ultimately, this review functions not only as a reference for comprehending the current state of remote sensing (RS) technologies but also as a framework for future research and development initiatives to address existing challenges and optimize the potential advantages of these revolutionary tools.</p>