Embodiments relate to systems and methods for self-adaptive episode mining under time threshold using delay estimation and temporal division. An episode mining engine can analyze a set of episodes captured from a set of network resources to detect all sequences of user-specified frequency within a supplied runtime budget or time threshold. The engine can achieve desired levels of completeness in the results by mining the input log file in multiple stages or steps, each having successively longer lengths of event sequences. After completion of each stage, the engine calculates a remaining amount of runtime budget, and updates the amount of time to be allocated for each of the remaining stages up to a generated maximum stage (or sequence length). The engine thus corrects the estimated remaining time in the runtime budget (or threshold) after each stage, and continues to the next stage until the runtime budget is consumed.