This thesis paper examines the causal effects of California Proposition 47, a criminal justice reform measure passed in 2014, on property crime rates in Los Angeles and other major cities in California. Proposition 47 aimed to reduce prison overcrowding by reclassifying certain nonviolent offenses as misdemeanors and reallocating resources to education, mental health, and drug treatment programs. Existing research on Proposition 47’s impact on property crime rates has yielded mixed results, primarily due to limitations inherent in observational studies. To overcome these limitations, this study employs a causal inference approach, especially focusing on difference in difference and synthetic control methods. A general reweighting approach to causal inference with time-series cross-sectional (TSCS) data from Chad Hazlet and Yiqing Xu is used too, including methods such as mean-balancing and kernel-balancing. We analyzed data from the FBI crime database spanning 11 years and covering 23 cities, focusing on property crimes such as burglary, larceny-theft, and motor vehicle theft. The synthetic control method allows for the estimation of the policy intervention’s effect by creating a synthetic control group that closely matches the characteristics of the treated group, addressing confounding factors. The study finds evidence that Propo- sition 47 increased property crime in Los Angeles and multiple major cities in California, supported by the average treatment effect on the treated (ATT) calculations and graphical representations. However, these conclusions rely on the assumptions made in the causal inference framework. Additionally, other studies indicate that Proposition 47 achieved de- carceration and reduced racial prejudices within the judicial system, emphasizing the need to consider broader social impacts. The results of this study should be interpreted with caution, and further exploration of Proposition 47’s long-term effects on the criminal justice system, communities, and individuals is necessary.