Probabilistic programs combine probabilistic reasoning models with Turing complete programming languages, unify formal descriptions of calculation and uncertain knowledge, and can effectively deal with complex relational models and uncertain problems. This study provides a tool for analyzing termination and assertions for affine probabilistic programs, namely, PROPER. On one hand, it can help to analyze the termination property of affine probabilistic programs both qualitatively and quantitatively. It can check whether a probabilistic program terminates with probability 1, estimate the upper bound of expected termination time, and calculate the number of steps after which the termination probability of the given probabilistic program decreases exponentially. On the other hand, it can estimate the correct probability interval for a given assertion to hold, which helps to analyze the influence of uncertainty of variables on the results of probabilistic programs. The experiments show that PROPER is effective for analyzing various affine probabilistic programs.