Traditional multi-target threat assessment algorithms typically rely on static situations-based binary decision-making, producing threat assessment results that reflect current conditions but fail to address complex, ambiguous, dynamic environments requiring subjective judgments. This paper introduces a multi-objective dynamic threat assessment approach grounded in three-way decision-making, incorporating prospect value theory and VIKOR (Vlsekreterne Indeks Kompromisno Reshenje) simulation framework. By processing time-series situation information into fuzzy sets, a comprehensive intuitionistic fuzzy information set is derived, and attribute weights are assigned. Subsequently, the conditional probability of target threats is determined using the VIKOR method. Ultimately, cumulative prospect values are computed based on prospect theory to establish three decision-making criteria for threat assessment and classification. Simulation demonstrates that the proposed method handles uncertain information in dynamic scenes, defines objective three-way classification criteria, prioritizes target threats, and quantifies decision-makers’ preferences through a fuzzy preference matrix.