The strategy of verbal self-defense plays an important role in parliamentary communication. This strategy is understood as an orientation of speech behavior that is realized through a finite set of objectively existing and statistically verifiable linguopragmatic mechanisms: defensive, constructive-balanced, agonistic, and mixed. However, the question of how these mechanisms are determined by party affiliation remains open. The aim of this study is to test the hypothesis that these mechanisms can be predicted with high accuracy on the basis of tactical profile and party affiliation. The theoretical framework of the analysis draws on the theory of speech strategies and tactics, pragmalinguistics, and corpus-informed discourse analysis. The corpus consists of 363 transcripts of Bundestag deputies' speeches from the 2025–2026 sessions. Each speech was annotated according to a formalized list of lexical and grammatical markers. Two classifiers (multinomial logistic regression and random forest) were compared on a full feature set (tactical frequencies and party indicators) and a reduced set (tactics only). The full model achieved perfect classification accuracy (1.00 under cross-validation). When party indicators were removed, accuracy decreased to 0.53–0.55, yet remained more than twice the chance level of 0.25. The results show that party affiliation acts as a decisive predictor fully accounting for the type of mechanism, with challenge and contrast serving as stylistic amplifiers rather than independent determinants. The identified mechanisms thus emerge not as analytical artifacts but as real, statistically robust patterns of speech behavior, shaped by the institutional role and ideological stance of each party.