This paper introduces PRIMA (Passive Reduced-order Interconnect Macromodeling Algorithm), an algorithm designed to generate provably passive reduced-order N-port models for RLC interconnect circuits. The authors emphasize the importance of passivity in ensuring overall circuit stability, especially when connected to other stable loads. PRIMA extends the Block Arnoldi technique to include guaranteed passivity, which is not possible with existing methods like MPVL. Empirical results show that PRIMA offers superior accuracy compared to Block Arnoldi and comparable accuracy to MPVL. The algorithm is efficient, particularly for large and complex RLC circuits, and can be integrated with path tracing algorithms from RICE to achieve high-frequency response approximations with excellent efficiency. The paper includes several examples demonstrating the effectiveness of PRIMA in various circuit configurations, including mesh ground planes, nonlinear drivers driving transmission lines, and coupled noise in a two-bit bus.This paper introduces PRIMA (Passive Reduced-order Interconnect Macromodeling Algorithm), an algorithm designed to generate provably passive reduced-order N-port models for RLC interconnect circuits. The authors emphasize the importance of passivity in ensuring overall circuit stability, especially when connected to other stable loads. PRIMA extends the Block Arnoldi technique to include guaranteed passivity, which is not possible with existing methods like MPVL. Empirical results show that PRIMA offers superior accuracy compared to Block Arnoldi and comparable accuracy to MPVL. The algorithm is efficient, particularly for large and complex RLC circuits, and can be integrated with path tracing algorithms from RICE to achieve high-frequency response approximations with excellent efficiency. The paper includes several examples demonstrating the effectiveness of PRIMA in various circuit configurations, including mesh ground planes, nonlinear drivers driving transmission lines, and coupled noise in a two-bit bus.