We consider the problem of estimating lead times of jobs that arrive dynamically in a production shop. The lead time of a job refers to the duration between the job's arrival and completion. To improve accuracy of estimation and generality of application, we propose a new rule that takes into account parallelization of waiting queues in the system and job-specific sequence of visiting workstations. We carry out extensive experiments to evaluate performance of the rule, and the results suggest that the rule is high-performing in production shops including single-machine shops, parallel-machine shops, flexible flow shops, and flexible job shops. We further provide the mean of best values found for the parameters in the proposed rule under three performance measures: relative error ratio, mean tardiness ratio, and percentage of tardy jobs, respectively, to help users determine the parameters according to their needs.