The current generation is under extreme pressure to find an effective way for disposal of existing plastic and a suitable, sustainable alternatives for plastic. During the recent past, natural fiber reinforced recycled plastic composites (NFCs) have emerged as a lucrative option to not only increase the life cycle of waste plastic but also provide a market for agriculture waste by utilizing fibers from crops as a reinforcement for these composites. Changing weather conditions, varied geographical locations and different harvesting techniques results in inherently inconsistent mechanical properties of natural fibers resulting in varied mechanical properties for NFCs. The main focus presented herein involves critically analyzing available data on natural fiber composites to develop usable statistical models to predict major mechanical properties for producing engineering properties or standards related to natural fiber composites. Available literature was reviewed with usable data pertaining to tensile properties of NFCs extracted and analyzed to generate property trends relating material composition and manufacturing parameters. Polynomial regression models were derived for predicting these properties for various processing conditions. For statistical modelling, fiber fraction (FF in w/o ), matrix strength (MS), matrix modulus (MM), and matrix elongation (ME) were used as continuous predictors whereas, fiber length (FLtype), fiber type (Ftype), processing method (Prmethod), and treated (Tr) or untreated (UTr) were entered as categorical predictors to predict tensile strength (T.S), tensile modulus (TM), and total elongation (TE) of natural fiber composites. The regression equation for tensile strength is: T. S (MPa)0.5 = 2.016 + 0.0329 FF (w/o ) + 0.07332 MS (MPa) + 0.0 UTr

• 0.3057 Tr + 0.0 FFlax + 0.028 FHemp + 0.210 FJute − 0.264 FSisal
• 0 FLGround − 0.039 FLLong + 0.787 FLmat + 0.537 FLMedium
• 0.081 FLShort + 0.0 PrCM − 0.820 PrHLU + 0.427 PrIM − 0.000551 (FF × FF) Similar equations for tensile modulus and total elongation were developed. Matrix strength (MS) and modulus (MM) were important predictors for predicting composite strength and modulus, and explained 82% and 60% of the variability, respectively. For elongation, the two major predictors, FLtype and ME, explained 60% of model variability and the contribution of FF was 20%. Model verification included test data set from the literature review and from experimental data of an innovative hemp fiber reinforced recycled grain bag composites manufactured for this thesis. The model accurately predicted within a 95% confidence interval. An effective tool for determining natural fiber composite properties was engineered. These property curves identified salient independent factors and can be used for engineering decisions pertaining to material selection, process selection, and other important design decisions during product development and production. Natural fiber composites can be effectively introduced as value added products from recycled plastic along with agricultural fibers for creating sustainable and more environmentally friendly economies with predictable mechanical properties.