Data mining is a process that involves extracting new, non-trivial information from huge datasets. This information can be used in a variety of applications. Several fields, including temporal pattern recognition, statistics, optimisation, temporal databases, high-performance computing, visualisation, and parallel computing, all meet in the rapidly developing field of temporal data mining. The growth of digital data and the processing power of computers have severely limited a field called data mining that integrates computer science and statistics. The software cost estimation category is one of data mining's disciplines. This study's primary objective is to comprehend the temporal mining methods currently in use in order to spot the gaps and flaws in the most recent software cost estimation technologies. This research also includes a concise summary of recent developments in the field of temporal data mining that has taken place recently. This study serves as a springboard for a discussion of the reasons why temporal data mining was required in the industry, which played a significant part in the development of the current generation of temporal data mining techniques for software cost assessment.